70 results on '"IMAGE processing"'
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2. MultiMedia Modeling : 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 – February 2, 2024, Proceedings, Part III
- Author
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Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata, Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, and Yoko Yamakata
- Subjects
- Computer vision, Image processing, Pattern recognition systems, Application software, Information storage and retrieval systems, Machine learning
- Abstract
This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29–February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.
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- 2024
3. MultiMedia Modeling : 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 – February 2, 2024, Proceedings, Part IV
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Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata, Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, and Yoko Yamakata
- Subjects
- Computer vision, Image processing, Pattern recognition systems, Application software, Information storage and retrieval systems, Machine learning
- Abstract
This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29–February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.
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- 2024
4. Wisdom, Well-Being, Win-Win : 19th International Conference, IConference 2024, Changchun, China, April 15–26, 2024, Proceedings, Part III
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Isaac Sserwanga, Hideo Joho, Jie Ma, Preben Hansen, Dan Wu, Masanori Koizumi, Anne J. Gilliland, Isaac Sserwanga, Hideo Joho, Jie Ma, Preben Hansen, Dan Wu, Masanori Koizumi, and Anne J. Gilliland
- Subjects
- Application software, Image processing, User interfaces (Computer systems), Human-computer interaction, Artificial intelligence
- Abstract
The Three-volume set LNCS 14596, 14597 and 14598 constitutes the proceedings of the 19th International Conference on Wisdom, Well-Being, Win-Win, iConference 2024, which was hosted virtually by University of Tsukuba, Japan and in presence by Jilin University, Changchun, China, during April 15–26, 2024. The 36 full papers and 55 short papers are presented in these proceedings were carefully reviewed and selected from 218 submissions. The papers are organized in the following topical sections: Volume I: Archives and Information Sustainability; Behavioural Research; AI and Machine Learning; Information Science and Data Science; Information and Digital Literacy. Volume II: Digital Humanities; Intellectual Property Issues; Social Media and Digital Networks; Disinformation and Misinformation; Libraries, Bibliometrics and Metadata. Volume III: Knowledge Management; Information Science Education; Information Governance and Ethics; Health Informatics; Human-AI Collaboration; Information Retrieval; Community Informatics; Scholarly, Communication and Open Access.
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- 2024
5. Multidimensional Signals, Augmented Reality and Information Technologies : Proceedings of 3DWCAI 2023
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Roumen Kountchev, Srikanta Patnaik, Wenfeng Wang, Roumiana Kountcheva, Roumen Kountchev, Srikanta Patnaik, Wenfeng Wang, and Roumiana Kountcheva
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- Control engineering, Robotics, Automation, Artificial intelligence, Image processing
- Abstract
This book features a collection of high-quality, peer-reviewed research papers presented at Second'World Conference on Intelligent and 3-D Technologies'(WCI3DT 2023), held in China during May 26–28, 2023. The book provides an opportunity to researchers and academia as well as practitioners from industry to publish their ideas and recent research development work on all aspects of 3D imaging technologies and artificial intelligence, their applications and other related areas. The book presents ideas and the works of scientists, engineers, educators and students from all over the world from institutions and industries.
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- 2024
6. Evolutionary Artificial Intelligence : Proceedings of ICEAI 2023
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David Asirvatham, Francisco M. Gonzalez-Longatt, Przemyslaw Falkowski-Gilski, R. Kanthavel, David Asirvatham, Francisco M. Gonzalez-Longatt, Przemyslaw Falkowski-Gilski, and R. Kanthavel
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- Computational intelligence, Artificial intelligence, Image processing, Algorithms
- Abstract
This book gathers a collection of selected works and new research results of scholars and graduate students presented at International Conference on Evolutionary Artificial Intelligence (ICEAI 2023) held in Malaysia during 13-14 September 2023. The focus of the book is interdisciplinary in nature and includes research on all aspects of evolutionary computation to find effective solutions to a wide range of computationally difficult problems. The book covers topics such as particle swarm optimization, evolutionary programming, genetic programming, hybrid evolutionary algorithms, ant colony optimization, evolutionary neural networks, evolutionary reinforcement learning, genetic algorithms, memetic algorithms, novel bio-inspired algorithms, evolving multi-agent systems, agent-based evolutionary approaches, and evolutionary game theory.
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- 2024
7. Image Processing and Machine Learning, Volume 2 : Advanced Topics in Image Analysis and Machine Learning
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Erik Cuevas, Alma Nayeli Rodríguez, Erik Cuevas, and Alma Nayeli Rodríguez
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- Image processing, Machine learning
- Abstract
Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1.Written with instructors and students of image processing in mind, this book's intuitive organization also contains appeal for app developers and engineers.
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- 2024
8. Video Object Tracking : Tasks, Datasets, and Methods
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Ning Xu, Weiyao Lin, Xiankai Lu, Yunchao Wei, Ning Xu, Weiyao Lin, Xiankai Lu, and Yunchao Wei
- Subjects
- Image processing, Image processing--Digital techniques, Computer vision, Automatic tracking, Digital video, Pattern recognition systems, Machine learning
- Abstract
This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a better understanding of the most important problems and developed technologies in the area. Video tracking is a key research area in computer vision and aims to track unique objects in a given video, which are useful for various applications such as video conference, video editing, surveillance, and autonomous driving. This book begins with an introduction to the task of video object tracking, including the most common problem settings. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of video tracking. The book includes these recent results as well as benchmarks in large-scale human-centric video analysis in complex events.
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- 2024
9. MultiMedia Modeling : 30th International Conference, MMM 2024, Amsterdam, The Netherlands, January 29 – February 2, 2024, Proceedings, Part I
- Author
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Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, Yoko Yamakata, Stevan Rudinac, Alan Hanjalic, Cynthia Liem, Marcel Worring, Björn Þór Jónsson, Bei Liu, and Yoko Yamakata
- Subjects
- Computer vision, Image processing, Pattern recognition systems, Application software, Information storage and retrieval systems, Machine learning
- Abstract
This book constitutes the refereed proceedings of the 30th International Conference on MultiMedia Modeling, MMM 2024, held in Amsterdam, The Netherlands, during January 29 – February 2, 2024.The 112 full papers included in this volume were carefully reviewed and selected from 297 submissions. The MMM conference were organized in topics related to multimedia modelling, particularly: audio, image, video processing, coding and compression; multimodal analysis for retrieval applications, and multimedia fusion methods.
- Published
- 2024
10. Deep Learning for Agricultural Visual Perception : Crop Pest and Disease Detection
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Rujing Wang, Lin Jiao, Kang Liu, Rujing Wang, Lin Jiao, and Kang Liu
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- Artificial intelligence, Image processing—Digital techniques, Computer vision, Machine learning, Image processing, Agriculture
- Abstract
This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.
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- 2023
11. A Unifying Framework for Formal Theories of Novelty : Discussions, Guidelines, and Examples for Artificial Intelligence
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Terrance Boult, Walter Scheirer, Terrance Boult, and Walter Scheirer
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- Computer vision, Machine learning, Image processing—Digital techniques, Pattern recognition systems, Image processing, Artificial intelligence
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This book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems. Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems. The book presents examples of using this framework to define and evaluate in multiple domains including image recognition image-based open world learning, hand-writing and author analysis, CartPole Control, Image Captioning, and Monopoly. Chapters are written by well-known contributors to this new and emerging field. In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games.
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- 2023
12. Convolutional Neural Networks for Medical Applications
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Teik Toe Teoh and Teik Toe Teoh
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- Computer vision, Medical sciences, Artificial intelligence, Machine learning, Image processing, Artificial intelligence—Data processing
- Abstract
Convolutional Neural Networks for Medical Applications consists of research investigated by the author, containing state-of-the-art knowledge, authored by Dr Teoh Teik Toe, in applying Convolutional Neural Networks (CNNs) to the medical imagery domain. This book will expose researchers to various applications and techniques applied with deep learning on medical images, as well as unique techniques to enhance the performance of these networks.Through the various chapters and topics covered, this book provides knowledge about the fundamentals of deep learning to a common reader while allowing a research scholar to identify some futuristic problem areas. The topics covered include brain tumor classification, pneumonia image classification, white blood cell classification, skin cancer classification and diabetic retinopathy detection. The first chapter will begin by introducing various topics used in training CNNs to help readers with common concepts covered across the book. Each chapter begins by providing information about the disease, its implications to the affected and how the use of CNNs can help to tackle issues faced in healthcare. Readers would be exposed to various performance enhancement techniques, which have been tried and tested successfully, such as specific data augmentations and image processing techniques utilized to improve the accuracy of the models.
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- 2023
13. Computer Vision : Applications of Visual AI and Image Processing
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Pancham Shukla, Rajanikanth Aluvalu, Shilpa Gite, Uma Maheswari, Pancham Shukla, Rajanikanth Aluvalu, Shilpa Gite, and Uma Maheswari
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- Artificial intelligence, Computer vision, Image processing
- Abstract
This book focuses on the latest developments in the fields of visual AI, image processing and computer vision. It shows research in basic techniques like image pre-processing, feature extraction, and enhancement, along with applications in biometrics, healthcare, neuroscience and forensics. The book highlights algorithms, processes, novel architectures and results underlying machine intelligence with detailed execution flow of models.
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- 2023
14. Cloud-Based Remote Sensing with Google Earth Engine : Fundamentals and Applications
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Jeffrey A. Cardille, Morgan A. Crowley, David Saah, Nicholas E. Clinton, Jeffrey A. Cardille, Morgan A. Crowley, David Saah, and Nicholas E. Clinton
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- Environmental monitoring, Image processing, Artificial intelligence—Data processing, Engineering—Data processing
- Abstract
This book guides its audience—which can range from novice users to experts— though a 55-chapter tour of Google Earth Engine. A sequenced and diverse set of lab materials, this is the product of more than a year of effort from more than a hundred individuals, collecting new exercises from professors, undergraduates, master's students, PhD students, postdocs, and independent consultants. Cloud Based Remote Sensing with Google Earth Engine is broadly organized into two halves. The first half, Fundamentals, is a set of 31 labs designed to take the reader from being a complete Earth Engine novice to being a quite advanced user. The second half, Applications, presents a tour of the world of Earth Engine across 24 chapters, showing how it is used in a very wide variety of settings that rely on remote-sensing data This is an open access book.
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- 2023
15. Document Layout Analysis
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Showmik Bhowmik and Showmik Bhowmik
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- Image processing, Pattern recognition systems, Machine learning
- Abstract
Document layout analysis (DLA) is a crucial step towards the development of an effective document image processing system. In the early days of document image processing, DLA was not considered as a complete and complex research problem, rather just a pre-processing step having some minor challenges. The main reason for that is the type of layout being considered for processing was simple. Researchers started paying attention to this complex problem as they come across a large variety of documents. This book presents a clear view of the past, present, and future of DLA, and it also discusses two recent methods developed to address the said problem.
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- 2023
16. Information for a Better World: Normality, Virtuality, Physicality, Inclusivity : 18th International Conference, IConference 2023, Virtual Event, March 13–17, 2023, Proceedings, Part I
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Isaac Sserwanga, Anne Goulding, Heather Moulaison-Sandy, Jia Tina Du, António Lucas Soares, Viviane Hessami, Rebecca D. Frank, Isaac Sserwanga, Anne Goulding, Heather Moulaison-Sandy, Jia Tina Du, António Lucas Soares, Viviane Hessami, and Rebecca D. Frank
- Subjects
- Application software, Computer networks, Image processing, User interfaces (Computer systems), Human-computer interaction, Artificial intelligence, Social sciences—Data processing
- Abstract
This two-volume set LNCS 13971 + 13972 constitutes the refereed proceedings of the 18th International Conference on Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, held in March 2023.The 36 full papers and the 46 short papers presented in these proceedings were carefully reviewed and selected from 197 submissions. They cover topics such as: Archives and Records, Behavioral Research, Information Governance and Ethics, AI and Machine Learning, Data Science, Information and Digital literacy, Cultural Perspectives, Knowledge Management and Intellectual Capital, Social Media and Digital Networks, Libraries, Human-Computer Interaction and Technology, Information Retrieval, Community Informatics, and Digital Information Infrastructure.
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- 2023
17. Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022)
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Peng You, Heng Li, Zhenxiang Chen, Peng You, Heng Li, and Zhenxiang Chen
- Subjects
- Signal processing, Image processing, Machine learning
- Abstract
This book is a collection of the papers accepted by the ICIVIS 2022—The International Conference on Image, Vision and Intelligent Systems, held on August 15–17, 2022, in Jinan, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state of practice in the topics covered by this conference proceedings.
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- 2023
18. Head and Neck Tumor Segmentation and Outcome Prediction : Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
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Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge, Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, and Adrien Depeursinge
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- Image processing—Digital techniques, Computer vision, Image processing, Machine learning, Bioinformatics
- Abstract
This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022.The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 883 delineated PET/CT images was made available for training.
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- 2023
19. GANs for Data Augmentation in Healthcare
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Arun Solanki, Mohd Naved, Arun Solanki, and Mohd Naved
- Subjects
- Medical informatics, Image processing, Machine learning
- Abstract
Computer-Assisted Diagnostics (CAD) using Convolutional Neural Network (CNN) model has become an important technology in the medical industry, improving the accuracy of diagnostics. However, the lack Magnetic Resonance Imaging (MRI) data leads to the failure of the depth study algorithm. Medical records are often different because of the cost of obtaining information and the time spent consuming the information. In general, clinical data is unreliable and therefore the training of neural network methods to distribute disease across classes does not yield the desired results. Data augmentation is often done by training data to solve problems caused by augmentation tasks such as scaling, cropping, flipping, padding, rotation, translation, affine transformation, and color augmentation techniques such as brightness, contrast, saturation, and hue. Data Augmentation and Segmentation imaging using GAN can be used to provide clear images of brain, liver, chest, abdomen, and liver on an MRI. In addition, GAN shows strong promise in the field of clinical image synthesis. In many cases, clinical evaluation is limited by a lack of data and/or the cost of actual information. GAN can overcome these problems by enabling scientists and clinicians to work on beautiful and realistic images. This can improve diagnosis, prognosis, and disease. Finally, GAN highlights the potential for location of patient information within the data. This is a beneficial clinical application of GAN because it can effectivelyprotect patient confidentiality. This book covers the application of GANs on medical imaging augmentation and segmentation.
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- 2023
20. Object Tracking Technology : Trends, Challenges and Applications
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Ashish Kumar, Rachna Jain, Ajantha Devi Vairamani, Anand Nayyar, Ashish Kumar, Rachna Jain, Ajantha Devi Vairamani, and Anand Nayyar
- Subjects
- Image processing, Image processing—Digital techniques, Computer vision, Machine learning
- Abstract
With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges. The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.
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- 2023
21. Data Analysis for Neurodegenerative Disorders
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Deepika Koundal, Deepak Kumar Jain, Yanhui Guo, Amira S. Ashour, Atef Zaguia, Deepika Koundal, Deepak Kumar Jain, Yanhui Guo, Amira S. Ashour, and Atef Zaguia
- Subjects
- Medical informatics, Image processing—Digital techniques, Computer vision, Image processing, Machine learning, Artificial intelligence—Data processing
- Abstract
This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders.This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features:● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection.● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders.● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.
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- 2023
22. Fine-Grained Image Analysis: Modern Approaches
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Xiu-Shen Wei and Xiu-Shen Wei
- Subjects
- Computer vision, Image processing—Digital techniques, Image processing, Pattern recognition systems, Machine learning, Artificial intelligence
- Abstract
This book provides a comprehensive overview of the fine-grained image analysis research and modern approaches based on deep learning, spanning the full range of topics needed for designing operational fine-grained image systems. The author begins by providing detailed background information on FGIA, focusing on recognition and retrieval. The author also provides the fundamentals of convolutional neural networks to further make it easier for readers to understand the technical content in the book. The book introduces the main technical paradigms, technological developments, and representative approaches of fine-grained image recognition and fine-grained image retrieval. The author covers multiple popular research topics and includes cross-domain knowledge. The book also highlights advanced applications and topics for future research.
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- 2023
23. Progress in Artificial Intelligence and Pattern Recognition : 8th International Congress on Artificial Intelligence and Pattern Recognition, IWAIPR 2023, Varadero, Cuba, September 27–29, 2023, Proceedings
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Yanio Hernández Heredia, Vladimir Milián Núñez, José Ruiz Shulcloper, Yanio Hernández Heredia, Vladimir Milián Núñez, and José Ruiz Shulcloper
- Subjects
- Computer vision, Image processing, Artificial intelligence
- Abstract
This book constitutes the refereed proceedings of the 8th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2023, held in Varadero, Cuba, in October 2023. The 68 papers presented in the proceedings set were carefully reviewed and selected from 38 submissions. The IWAIPR conference aims to provide a leading international forum to promote and disseminate ongoing research into mathematical methods of computing techniques for Artifical Intelligence and Pattern Recognition.
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- 2023
24. Digital Watermarking for Machine Learning Model : Techniques, Protocols and Applications
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Lixin Fan, Chee Seng Chan, Qiang Yang, Lixin Fan, Chee Seng Chan, and Qiang Yang
- Subjects
- Machine learning, Data protection, Image processing—Digital techniques, Computer vision, Image processing
- Abstract
Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
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- 2023
25. Proceedings of the World Conference on Intelligent and 3-D Technologies (WCI3DT 2022) : Methods, Algorithms and Applications
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Roumen Kountchev, Kazumi Nakamatsu, Wenfeng Wang, Roumiana Kountcheva, Roumen Kountchev, Kazumi Nakamatsu, Wenfeng Wang, and Roumiana Kountcheva
- Subjects
- Control engineering, Robotics, Automation, Artificial intelligence, Image processing
- Abstract
This book features a collection of high-quality, peer-reviewed research papers presented at first ‘World Conference on Intelligent and 3-D Technologies'(WCI3DT 2022), held in China during May 24–26, 2022. The book provides an opportunity for the researchers and academia as well as practitioners from industry to publish their ideas and recent research development work on all aspects of 3D imaging technologies and artificial intelligence, their applications, and other related areas. The book presents ideas and the works of scientists, engineers, educators, and students from all over the world from institutions and industries.
- Published
- 2023
26. Computational Vision and Bio-Inspired Computing : Proceedings of ICCVBIC 2021
- Author
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S. Smys, João Manuel R. S. Tavares, Valentina Emilia Balas, S. Smys, João Manuel R. S. Tavares, and Valentina Emilia Balas
- Subjects
- Computational intelligence, Bioinformatics, Image processing—Digital techniques, Computer vision, Image processing
- Abstract
This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.
- Published
- 2022
27. The International Conference on Image, Vision and Intelligent Systems (ICIVIS 2021)
- Author
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Jian Yao, Yang Xiao, Peng You, Guang Sun, Jian Yao, Yang Xiao, Peng You, and Guang Sun
- Subjects
- Signal processing, Image processing, Machine learning
- Abstract
This book is a collection of the papers accepted by the ICIVIS 2021—The International Conference on Image, Vision and Intelligent Systems held on June 15–17, 2021, in Changsha, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings.
- Published
- 2022
28. Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
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Maki K. Habib and Maki K. Habib
- Subjects
- Affect (Psychology)--Data processing, Artificial life, Automatic machinery, Artificial intelligence--Industrial applications, Machine learning, Image processing
- Abstract
As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.
- Published
- 2022
29. Image Analysis and Processing. ICIAP 2022 Workshops : ICIAP International Workshops, Lecce, Italy, May 23–27, 2022, Revised Selected Papers, Part II
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Pier Luigi Mazzeo, Emanuele Frontoni, Stan Sclaroff, Cosimo Distante, Pier Luigi Mazzeo, Emanuele Frontoni, Stan Sclaroff, and Cosimo Distante
- Subjects
- Image processing—Digital techniques, Computer vision, Image processing, Machine learning, Computer networks
- Abstract
The two-volume set LNCS 13373 and 13374 constitutes the papers of several workshops which were held in conjunction with the 21st International Conference on Image Analysis and Processing, ICIAP 2022, held in Lecce, Italy, in May 2022.The 96 revised full papers presented in the proceedings set were carefully reviewed and selected from 157 submissions.ICIAP 2022 presents the following Sixteen workshops:Volume I:GoodBrother workshop on visual intelligence for active and assisted livingParts can worth like the Whole - PART 2022Workshop on Fine Art Pattern Extraction and Recognition - FAPERWorkshop on Intelligent Systems in Human and Artificial Perception - ISHAPE 2022Artificial Intelligence and Radiomics in Computer-Aided Diagnosis - AIRCADDeep-Learning and High Performance Computing to Boost Biomedical Applications - DeepHealthVolume II: Human Behaviour Analysis for Smart City Environment Safety - HBAxSCESBinary is the new Black (and White): Recent Advances on Binary Image ProcessingArtificial Intelligence for preterm infants'healthCare - AI-careTowards a Complete Analysis of People: From Face and Body to Clothes - T-CAPArtificial Intelligence for Digital Humanities - AI4DHMedical Transformers - MEDXFLearning in Precision Livestock Farming - LPLFWorkshop on Small-Drone Surveillance, Detection and Counteraction Techniques - WOSDETCMedical Imaging Analysis For Covid-19 - MIACOVID 2022Novel Benchmarks and Approaches for Real-World Continual Learning - CL4REAL
- Published
- 2022
30. Multimedia Forensics
- Author
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Husrev Taha Sencar, Luisa Verdoliva, Nasir Memon, Husrev Taha Sencar, Luisa Verdoliva, and Nasir Memon
- Subjects
- Data protection, Computer vision, Image processing, Machine learning, Multimedia systems
- Abstract
This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field.
- Published
- 2022
31. Intelligent Healthcare : Infrastructure, Algorithms and Management
- Author
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Chinmay Chakraborty, Mohammad R. Khosravi, Chinmay Chakraborty, and Mohammad R. Khosravi
- Subjects
- Medical informatics, Computational intelligence, Internet of things, Biomedical engineering, Image processing, Computers and civilization
- Abstract
The book Intelligent Healthcare: Infrastructure, Algorithms, and Management® cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning.This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors.Main Features:Ø Immersive technologies in healthcareØ Internet of medical thingsØ Federated learning algorithmsØ Explainable AI in Pervasive HealthcareØ New management principles using biomedical dataØ Secured healthcare management systemsThis book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.
- Published
- 2022
32. Nonlinear Dimensionality Reduction Techniques : A Data Structure Preservation Approach
- Author
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Sylvain Lespinats, Benoit Colange, Denys Dutykh, Sylvain Lespinats, Benoit Colange, and Denys Dutykh
- Subjects
- Machine learning, Artificial intelligence—Data processing, Image processing
- Abstract
This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.
- Published
- 2021
33. Trends and Advancements of Image Processing and Its Applications
- Author
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Prashant Johri, Mario José Diván, Ruqaiya Khanam, Marcelo Marciszack, Adrián Will, Prashant Johri, Mario José Diván, Ruqaiya Khanam, Marcelo Marciszack, and Adrián Will
- Subjects
- Image processing, Signal processing, Control engineering, Robotics, Automation, Artificial intelligence
- Abstract
This book covers current technological innovations and applications in image processing, introducing analysis techniques and describing applications in remote sensing and manufacturing, among others. The authors include new concepts of color space transformation like color interpolation, among others. Also, the concept of Shearlet Transform and Wavelet Transform and their implementation are discussed. The authors include a perspective about concepts and techniques of remote sensing like image mining, geographical, and agricultural resources. The book also includes several applications of human organ biomedical image analysis. In addition, the principle of moving object detection and tracking — including recent trends in moving vehicles and ship detection – is described.Presents developments of current research in various areas of image processing;Includes applications of image processing in remote sensing, astronomy, and manufacturing;Pertains to researchers, academics, students, and practitioners in image processing.
- Published
- 2021
34. Recommender Systems in Fashion and Retail
- Author
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Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, Reza Shirvany, Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, and Reza Shirvany
- Subjects
- Data mining, Artificial intelligence, Computational intelligence, Electronic commerce, Building materials, Image processing
- Abstract
This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
- Published
- 2021
35. Artificial Intelligence in Breast Cancer Early Detection and Diagnosis
- Author
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Khalid Shaikh, Sabitha Krishnan, Rohit Thanki, Khalid Shaikh, Sabitha Krishnan, and Rohit Thanki
- Subjects
- Artificial intelligence--Medical applications, Image processing, Breast--Cancer--Diagnosis--Data processing, Diagnostic imaging--Data processing, Machine learning
- Abstract
This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer.Discusses various existing screening methods for breast cancerPresents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics
- Published
- 2021
36. Intelligent Life System Modelling, Image Processing and Analysis : 7th International Conference on Life System Modeling and Simulation, LSMS 2021 and 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, Hangzhou, China, October 30 – November 1, 2021, Proceedings, Part
- Author
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Minrui Fei, Luonan Chen, Shiwei Ma, Xin Li, Minrui Fei, Luonan Chen, Shiwei Ma, and Xin Li
- Subjects
- Computer simulation, Machine learning, Image processing, Database management, Computer systems, Computer networks
- Abstract
This three-volume set CCIS 1467, CCIS 1468, and CCIS 1469 constitutes the thoroughly refereed proceedings of the 7th International Conference on Life System Modeling and Simulation, LSMS 2021, and of the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, held in Hangzhou, China, in October 2021. The 159 revised papers presented were carefully reviewed and selected from over 430 submissions.The papers of this volume are organized in topical sections on: Medical Imaging and Analysis Using Intelligence Computing; Biomedical signal processing, imaging, visualization and surgical robotics; Computational method in taxonomy study and neural dynamics; Intelligent medical apparatus, clinical applications and intelligent design of biochips; Power and Energy Systems; Computational Intelligence in Utilization of Clean and Renewable Energy Resources, and Intelligent Modelling, Control and Supervision for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Control Methods in Energy Infrastructure Development and Distributed Power Generation Systems; Intelligent Modeling, Simulation and Control of Power Electronics and Power Networks; Intelligent Techniques for Sustainable Energy and Green Built Environment, Water Treatment and Waste Management; Intelligent Robot and Simulation; Intelligent Data Processing, Analysis and Control in Complex Systems; Advanced Neural Network Theory and Algorithms; Advanced Computational Methods and Applications; Fuzzy, Neural, and Fuzzy-neuro Hybrids; Intelligent Modelling, Monitoring, and Control of Complex Nonlinear Systems; Intelligent manufacturing, autonomous systems, intelligent robotic systems; Computational Intelligence and Applications.
- Published
- 2021
37. Programming with TensorFlow : Solution for Edge Computing Applications
- Author
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Kolla Bhanu Prakash, G. R. Kanagachidambaresan, Kolla Bhanu Prakash, and G. R. Kanagachidambaresan
- Subjects
- Signal processing, Image processing, Speech processing systems, Neural networks (Computer science), Machine learning, Python (Computer program language), Computational intelligence, Programming languages (Electronic computers)
- Abstract
This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs).
- Published
- 2021
38. Games and Learning Alliance : 9th International Conference, GALA 2020, Laval, France, December 9–10, 2020, Proceedings
- Author
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Iza Marfisi-Schottman, Francesco Bellotti, Ludovic Hamon, Roland Klemke, Iza Marfisi-Schottman, Francesco Bellotti, Ludovic Hamon, and Roland Klemke
- Subjects
- Microcomputers, Education—Data processing, Artificial intelligence, Computer vision, Image processing, Computer networks
- Abstract
This book constitutes the refereed proceedings of the 9th International Conference on Games and Learning Alliance, GALA 2020, held in Laval, France, in December 2020. The 35 full papers and 10 short papers were carefully reviewed and selected from 77 submissions. The papers cover a broad spectrum of topics: Serious Game Design; Serious Game Analytics; Virtual and Mixed Reality Applications; Gamification Theory; Gamification Applications; Serious Games for Instruction; and Serious Game Applications and Studies.
- Published
- 2020
39. Intelligent Systems : 9th Brazilian Conference, BRACIS 2020, Rio Grande, Brazil, October 20–23, 2020, Proceedings, Part I
- Author
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Ricardo Cerri, Ronaldo C. Prati, Ricardo Cerri, and Ronaldo C. Prati
- Subjects
- Artificial intelligence, Social sciences—Data processing, Education—Data processing, Data mining, Image processing, Computer vision
- Abstract
The two-volume set LNAI 12319 and 12320 constitutes the proceedings of the 9th Brazilian Conference on Intelligent Systems, BRACIS 2020, held in Rio Grande, Brazil, in October 2020. The total of 90 papers presented in these two volumes was carefully reviewed and selected from 228 submissions. The contributions are organized in the following topical section: Part I: Evolutionary computation, metaheuristics, constrains and search, combinatorial and numerical optimization; neural networks, deep learning and computer vision; and text mining and natural language processing. Part II: Agent and multi-agent systems, planning and reinforcement learning; knowledge representation, logic and fuzzy systems; machine learning and data mining; and multidisciplinary artificial and computational intelligence and applications.Due to the Corona pandemic BRACIS 2020 was held as a virtual event.
- Published
- 2020
40. Stereoscopic Image Quality Assessment
- Author
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Yong Ding, Guangming Sun, Yong Ding, and Guangming Sun
- Subjects
- Image processing, Image processing—Digital techniques, Computer vision, Database management, Artificial intelligence, Electronics, Measurement, Measuring instruments
- Abstract
This book provides a comprehensive review of all aspects relating to visual quality assessment for stereoscopic images, including statistical mathematics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and analyzing the current state-of-the-art in SIQA algorithms, the latest challenges and research directions as well as novel models and paradigms. In addition, a large number of vivid figures and formulas help readers gain a deeper understanding of the foundation and new applications of objective stereoscopic image quality assessment technologies.Reviewing the latest advances, challenges and trends in stereoscopic image quality assessment, this book is a valuable resource for researchers, engineers andgraduate students working in related fields, including imaging, displaying and image processing, especially those interested in SIQA research.
- Published
- 2020
41. Python Image Processing Cookbook : Over 60 Recipes to Help You Perform Complex Image Processing and Computer Vision Tasks with Ease
- Author
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Sandipan Dey and Sandipan Dey
- Subjects
- Python (Computer program language), Image processing, Machine learning, Computer vision
- Abstract
Explore Keras, scikit-image, open source computer vision (OpenCV), Matplotlib, and a wide range of other Python tools and frameworks to solve real-world image processing problemsKey FeaturesDiscover solutions to complex image processing tasks using Python tools such as scikit-image and KerasLearn popular concepts such as machine learning, deep learning, and neural networks for image processingExplore common and not-so-common challenges faced in image processingBook DescriptionWith the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing.With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems.By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.What you will learnImplement supervised and unsupervised machine learning algorithms for image processingUse deep neural network models for advanced image processing tasksPerform image classification, object detection, and face recognitionApply image segmentation and registration techniques on medical images to assist doctorsUse classical image processing and deep learning methods for image restorationImplement text detection in images using Tesseract, the optical character recognition (OCR) engineUnderstand image enhancement techniques such as gradient blendingWho this book is forThis book is for image processing engineers, computer vision engineers, software developers, machine learning engineers, or anyone who wants to become well-versed with image processing techniques and methods using a recipe-based approach. Although no image processing knowledge is expected, prior Python coding experience is necessary to understand key concepts covered in the book.
- Published
- 2020
42. Real-Time IoT Imaging with Deep Neural Networks : Using Java on the Raspberry Pi 4
- Author
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Nicolas Modrzyk and Nicolas Modrzyk
- Subjects
- Raspberry Pi (Computer), Image processing, Neural networks (Computer science)
- Abstract
This book shows you how to build real-time image processing systems all the way through to house automation. Find out how you can develop a system based on small 32-bit ARM processors that gives you complete control through voice commands.Real-time image processing systems are utilized in a wide variety of applications, such as in traffic monitoring systems, medical image processing, and biometric security systems. In Real-Time IoT Imaging with Deep Neural Networks, you will learn how to make use of the best DNN models to detect object in images using Java and a wrapper for OpenCV. Take a closer look at how Java scripting works on the Raspberry Pi while preparing your Visual Studio code for remote programming. You will also gain insights on image and video scripting. Author Nicolas Modrzyk shows you how to use the Rhasspy voice platform to add a powerful voice assistant and completely run and control your Raspberry Pi from your computer. To get your voice intents for house automation ready, you will explore how Java connects to the MQTT and handles parametrized Rhasspy voice commands. With your voice-controlled system ready for operation, you will be able to perform simple tasks such as detecting cats, people, and coffee pots in your selected environment. Privacy and freedom are essential, so priority is given to using open source software and an on-device voice environment where you have full control of your data and video streams. Your voice commands are your own—and just your own.With recent advancements in the Internet of Things and machine learning, cutting edge image processing systems provide complete process automation. This practical book teaches you to build such a system, giving you complete control with minimal effort.What You Will Learn:Show mastery by creating OpenCV filtersExecute a YOLO DNN model for image detectionApply the best Java scriptingon Raspberry Pi 4Prepare your setup for real-time remote programmingUse the Rhasspy voice platform for handling voice commands and enhancing your house automation setupWho This Book Is For:Engineers, and Hobbyists wanting to use their favorite JVM to run Object Detection and Networks on a Raspberry Pi
- Published
- 2020
43. Domain Adaptation in Computer Vision with Deep Learning
- Author
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Hemanth Venkateswara, Sethuraman Panchanathan, Hemanth Venkateswara, and Sethuraman Panchanathan
- Subjects
- Signal processing, Image processing, Artificial intelligence, Machine learning, Computer vision, Optical data processing
- Abstract
This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.
- Published
- 2020
44. Hyperspectral Image Analysis : Advances in Machine Learning and Signal Processing
- Author
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Saurabh Prasad, Jocelyn Chanussot, Saurabh Prasad, and Jocelyn Chanussot
- Subjects
- Image processing, Hyperspectral imaging
- Abstract
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas ofimage analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
- Published
- 2020
45. TinyML : Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
- Author
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Pete Warden, Daniel Situnayake, Pete Warden, and Daniel Situnayake
- Subjects
- Image processing, Computers, Electronic digital computers
- Abstract
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary.Build a speech recognizer, a camera that detects people, and a magic wand that responds to gesturesWork with Arduino and ultra-low-power microcontrollersLearn the essentials of ML and how to train your own modelsTrain models to understand audio, image, and accelerometer dataExplore TensorFlow Lite for Microcontrollers, Google's toolkit for TinyMLDebug applications and provide safeguards for privacy and securityOptimize latency, energy usage, and model and binary size
- Published
- 2019
46. Machine Learning for OpenCV 4 : Intelligent Algorithms for Building Image Processing Apps Using OpenCV 4, Python, and Scikit-learn, 2nd Edition
- Author
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Aditya Sharma, Vishwesh Ravi Shrimali, Michael Beyeler, Aditya Sharma, Vishwesh Ravi Shrimali, and Michael Beyeler
- Subjects
- OpenCV (Computer program language), Python (Computer program language), Machine learning, Image processing
- Abstract
A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4Key FeaturesGain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learnGet up to speed with Intel OpenVINO and its integration with OpenCV 4Implement high-performance machine learning models with helpful tips and best practicesBook DescriptionOpenCV is an opensource library for building computer vision apps. The latest release, OpenCV 4, offers a plethora of features and platform improvements that are covered comprehensively in this up-to-date second edition.You'll start by understanding the new features and setting up OpenCV 4 to build your computer vision applications. You will explore the fundamentals of machine learning and even learn to design different algorithms that can be used for image processing. Gradually, the book will take you through supervised and unsupervised machine learning. You will gain hands-on experience using scikit-learn in Python for a variety of machine learning applications. Later chapters will focus on different machine learning algorithms, such as a decision tree, support vector machines (SVM), and Bayesian learning, and how they can be used for object detection computer vision operations. You will then delve into deep learning and ensemble learning, and discover their real-world applications, such as handwritten digit classification and gesture recognition. Finally, you'll get to grips with the latest Intel OpenVINO for building an image processing system.By the end of this book, you will have developed the skills you need to use machine learning for building intelligent computer vision applications with OpenCV 4.What you will learnUnderstand the core machine learning concepts for image processingExplore the theory behind machine learning and deep learning algorithm designDiscover effective techniques to train your deep learning modelsEvaluate machine learning models to improve the performance of your modelsIntegrate algorithms such as support vector machines and Bayes classifier in your computer vision applicationsUse OpenVINO with OpenCV 4 to speed up model inferenceWho this book is forThis book is for Computer Vision professionals, machine learning developers, or anyone who wants to learn machine learning algorithms and implement them using OpenCV 4. If you want to build real-world Computer Vision and image processing applications powered by machine learning, then this book is for you. Working knowledge of Python programming is required to get the most out of this book.
- Published
- 2019
47. Building Computer Vision Projects with OpenCV 4 and C++ : Implement Complex Computer Vision Algorithms and Explore Deep Learning and Face Detection
- Author
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David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot, David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, and Roy Shilkrot
- Subjects
- OpenCV (Computer program language), Computer vision, Computer algorithms, Image processing
- Abstract
Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithmsKey FeaturesDiscover best practices for engineering and maintaining OpenCV projectsExplore important deep learning tools for image classificationUnderstand basic image matrix formats and filtersBook DescriptionOpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books:Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán EscriváLearn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek JoshiWhat you will learnStay up-to-date with algorithmic design approaches for complex computer vision tasksWork with OpenCV's most up-to-date API through various projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay augmented reality (AR) using the ArUco moduleCreate CMake scripts to compile your C++ applicationExplore segmentation and feature extraction techniquesRemove backgrounds from static scenes to identify moving objects for surveillanceWork with new OpenCV functions to detect and recognize text with TesseractWho this book is forIf you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.
- Published
- 2019
48. RGB-D Image Analysis and Processing
- Author
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Paul L. Rosin, Yu-Kun Lai, Ling Shao, Yonghuai Liu, Paul L. Rosin, Yu-Kun Lai, Ling Shao, and Yonghuai Liu
- Subjects
- Image analysis, Image processing
- Abstract
This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
- Published
- 2019
49. Computer Vision Projects with OpenCV and Python 3 : Six End-to-end Projects Built Using Machine Learning with OpenCV, Python, and TensorFlow
- Author
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Matthew Rever and Matthew Rever
- Subjects
- Computer vision, OpenCV (Computer program language), Python (Computer program language), Machine learning, Image processing
- Abstract
Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videosKey FeaturesImplement image classification and object detection using machine learning and deep learningPerform image classification, object detection, image segmentation, and other Computer Vision tasksCrisp content with a practical approach to solving real-world problems in Computer VisionBook DescriptionPython is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google's Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.What you will learnInstall and run major Computer Vision packages within PythonApply powerful support vector machines for simple digit classificationUnderstand deep learning with TensorFlowBuild a deep learning classifier for general imagesUse LSTMs for automated image captioningRead text from real-world imagesExtract human pose data from imagesWho this book is forPython programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
- Published
- 2018
50. Computer Vision in Control Systems-3 : Aerial and Satellite Image Processing
- Author
-
Margarita N. Favorskaya, Lakhmi C. Jain, Margarita N. Favorskaya, and Lakhmi C. Jain
- Subjects
- Image processing, Remote-sensing images, Computer vision, Computational intelligence
- Abstract
The research book is a continuation of the authors'previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms.The book gathers selected contributions addressing aerial and satellite image processing and related fields. Topics covered include novel tensor and wave models, a new comparative morphology scheme, warping compensation in video stabilization, image deblurring based on physical processes of blur impacts, and a rapid and robust core structural verification algorithm for feature extraction in images and videos, among others. All chapters focus on practical implementations. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, this book offers a timely guide.
- Published
- 2018
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