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90 results on '"Pelusi, Danilo"'

1. Improved optimizer with deep learning model for emotion detection and classification.

Author

Joseph CW, Kathrine GJW, Vimal S, Sumathi S, Pelusi D, Valencia XPB, and Verdú E

Subjects
Humans, Image Processing, Computer-Assisted methods, Neural Networks, Computer, Databases, Factual, Pattern Recognition, Automated methods, Face, Reproducibility of Results, Deep Learning, Emotions, Algorithms, Facial Expression
Abstract

Facial emotion recognition (FER) is largely utilized to analyze human emotion in order to address the needs of many real-time applications such as computer-human interfaces, emotion detection, forensics, biometrics, and human-robot collaboration. Nonetheless, existing methods are mostly unable to offer correct predictions with a minimum error rate. In this paper, an innovative facial emotion recognition framework, termed extended walrus-based deep learning with Botox feature selection network (EWDL-BFSN), was designed to accurately detect facial emotions. The main goals of the EWDL-BFSN are to identify facial emotions automatically and effectively by choosing the optimal features and adjusting the hyperparameters of the classifier. The gradient wavelet anisotropic filter (GWAF) can be used for image pre-processing in the EWDL-BFSN model. Additionally, SqueezeNet is used to extract significant features. The improved Botox optimization algorithm (IBoA) is then used to choose the best features. Lastly, FER and classification are accomplished through the use of an enhanced optimization-based kernel residual 50 (EK-ResNet50) network. Meanwhile, a nature-inspired metaheuristic, walrus optimization algorithm (WOA) is utilized to pick the hyperparameters of EK-ResNet50 network model. The EWDL-BFSN model was trained and tested with publicly available CK+ and FER-2013 datasets. The Python platform was applied for implementation, and various performance metrics such as accuracy, sensitivity, specificity, and F1-score were analyzed with state-of-the-art methods. The proposed EWDL-BFSN model acquired an overall accuracy of 99.37 and 99.25% for both CK+ and FER-2013 datasets and proved its superiority in predicting facial emotions over state-of-the-art methods.

Published
2024
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2. An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets.

Author

Swapnarekha H, Nayak J, Behera HS, Dash PB, and Pelusi D

Subjects
Humans, Sentiment Analysis, Algorithms, Fear, COVID-19, Deep Learning
Abstract

The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over the world. As of December 31, 2021, more than 2, 86, 901, 222 people have been infected with COVID-19. The rise in the number of COVID-19 cases and deaths across the world has caused fear, anxiety and depression among individuals. Social media is the most dominant tool that disturbed human life during this pandemic. Among the social media platforms, Twitter is one of the most prominent and trusted social media platforms. To control and monitor the COVID-19 infection, it is necessary to analyze the sentiments of people expressed on their social media platforms. In this study, we proposed a deep learning approach known as a long short-term memory (LSTM) model for the analysis of tweets related to COVID-19 as positive or negative sentiments. In addition, the proposed approach makes use of the firefly algorithm to enhance the overall performance of the model. Further, the performance of the proposed model, along with other state-of-the-art ensemble and machine learning models, has been evaluated by using performance metrics such as accuracy, precision, recall, the AUC-ROC and the F1-score. The experimental results reveal that the proposed LSTM + Firefly approach obtained a better accuracy of 99.59% when compared with the other state-of-the-art models.

Published
2023
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3. Artificial Intelligence-Based Cyber Security Applications

Author

Potula, Sri Rupin, Selvanambi, Ramani, Karuppiah, Marimuthu, Pelusi, Danilo, Kumar, Amit, Series Editor, Suganthan, Ponnuthurai Nagaratnam, Series Editor, Haase, Jan, Series Editor, Senatore, Sabrina, Editorial Board Member, Gao, Xiao-Zhi, Editorial Board Member, Mozar, Stefan, Editorial Board Member, Srivastava, Pradeep Kumar, Editorial Board Member, Sarveshwaran, Velliangiri, editor, Chen, Joy Iong-Zong, editor, and Pelusi, Danilo, editor

Published
2023
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4. Predicting New York Taxi Trip Duration Based on Regression Analysis Using ML and Time Series Forecasting Using DL

Author

Ramani, S., Ghiya, Anish, Aravind, Pusuluri Sidhartha, Karuppiah, Marimuthu, Pelusi, Danilo, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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7. Guest Editorial — Introduction to the Special Issue on Smart Fuzzy Optimization for Decision-Making in Uncertain Environments.

Author

Joo, Er Meng, Pelusi, Danilo, and Wen, Shiping

Subjects
*SWARM intelligence, *INFORMATION technology, *CONVOLUTIONAL neural networks, *MACHINE learning, *OPTIMIZATION algorithms, *DEEP learning, *METAHEURISTIC algorithms
Abstract

For managing data redundancy, the proposed Intelligent Data Fusion Technique (IDFT) decreases the quantity of transmitting data, broadens the network life cycle, enhances bandwidth utilization, and therefore resolves the energy and bandwidth usage bottleneck. Over the last five decades, fuzzy optimization has found numerous successful applications in diverse fields including operations research, manufacturing, information technology, energy optimization, data science and smart cities, big data analytics, etc. Fuzzy optimization is one kind of approximation of nonlinear optimization techniques, which has formed some systematic but not unified theories of fuzzy systems and other fuzzy-set-based methodologies. [Extracted from the article]

Published
2023
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8. Special issue on machine learning for security and privacy: advancing the state-of-the-art applications.

Author

Nayak, Janmenjoy, Al-Dabass, David, Pelusi, Danilo, and Mishra, Manohar

Subjects
DEEP learning, MACHINE learning, PRIVACY, QUALITY of life, UNIFORM Resource Locators, DISCRETE wavelet transforms
Abstract

In the past 10 years, several techniques have been proposed to address the security and privacy issues of smart systems. Sahin et al. have developed a machine learning-based malware detection system for differentiating Android malware from benign applications. [Extracted from the article]

Published
2023
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9. Improving Facial Emotion Recognition Using Residual Autoencoder Coupled Affinity Based Overlapping Reduction.

Author

Chatterjee, Sankhadeep, Das, Asit Kumar, Nayak, Janmenjoy, and Pelusi, Danilo

Subjects
EMOTION recognition, EMOTIONS, COMPUTER vision, FACIAL expression, DEEP learning
Abstract

Emotion recognition using facial images has been a challenging task in computer vision. Recent advancements in deep learning has helped in achieving better results. Studies have pointed out that multiple facial expressions may present in facial images of a particular type of emotion. Thus, facial images of a category of emotion may have similarity to other categories of facial images, leading towards overlapping of classes in feature space. The problem of class overlapping has been studied primarily in the context of imbalanced classes. Few studies have considered imbalanced facial emotion recognition. However, to the authors' best knowledge, no study has been found on the effects of overlapped classes on emotion recognition. Motivated by this, in the current study, an affinity-based overlap reduction technique (AFORET) has been proposed to deal with the overlapped class problem in facial emotion recognition. Firstly, a residual variational autoencoder (RVA) model has been used to transform the facial images to a latent vector form. Next, the proposed AFORET method has been applied on these overlapped latent vectors to reduce the overlapping between classes. The proposed method has been validated by training and testing various well known classifiers and comparing their performance in terms of a well known set of performance indicators. In addition, the proposed AFORET method is compared with already existing overlap reduction techniques, such as the OSM, ν -SVM, and NBU methods. Experimental results have shown that the proposed AFORET algorithm, when used with the RVA model, boosts classifier performance to a greater extent in predicting human emotion using facial images. [ABSTRACT FROM AUTHOR]

Published
2022
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10. Special issue on "Big Data Analytics and Deep Learning for E-Business Outcomes".

Author

Balakrishnan, Nagaraj, Pelusi, Danilo, and Ganesan, Subramaniam

Subjects
DEEP learning, ELECTRONIC commerce, BIG data, BUSINESS success, INFORMATION resources management
Abstract

Therefore, these data need Big Data Analysts and Data Scientists. Intelligent Computing can be enhanced with the Big Data analytics to enable and interpret large unstructured real-world data and intelligently react to all the entities or events. This special issue carries the solutions for the supply chain management, fraud detection, merchant analytics, recommender system and more based on big data analytics and deep learning methodologies. [Extracted from the article]

Published
2020
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11. Intelligent food processing: Journey from artificial neural network to deep learning.

Author

Nayak, Janmenjoy, Vakula, Kanithi, Dinesh, Paidi, Naik, Bighnaraj, and Pelusi, Danilo

Subjects
ARTIFICIAL neural networks, FOOD industry, DEEP learning, MACHINE learning, ACQUISITION of data, FOOD dehydration
Abstract

Since its initiation, ANN became popular and also plays a key role in enhancing the latest technology. With an increase in industrial automation and the Internet of Things, now it is easier than ever to collect data and monitor food drying, extrusion, and sterilization, etc. In this industrial revolution, the uses of ANN are found successful in food processing tasks like food grading, safety, and quality check, etc. In recent years, attention on shallow learning approach (i.e. use of earlier developed ANNs) in food processing is escalating as researchers found it extensive exploitation in resolving a lot of complex real-world problems in food processing. In this row, deep learning techniques have not left any stone unturned in the context of intelligent food processing paradigm. In this paper, a detailed analysis has been reported on the advancements of food processing using ANNs, which include the details journey from shallow learning to deep learning in the applications space. Such fusion of technology with the forefront of machine learning, deep learning, and image processing for food processing, is not just the mixture of hybrid concepts, rather it provides a scope to create new dimensions and growth opportunities for each innovation. [ABSTRACT FROM AUTHOR]

Published
2020
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13. Alzheimer’s Disease Detection Using Convolution Neural Networks

Author

Swapna, M., Ravali, M., Pavani, G., Prasad, M Shiva Durga, Kumar, V Pradeep, Nanda, Ashok Kumar, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Satheeskumaran, S., editor, Zhang, Yudong, editor, Balas, Valentina Emilia, editor, Hong, Tzung-pei, editor, and Pelusi, Danilo, editor

Published
2024
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14. Facial Emotion Recognition Using Deep Learning

Author

Selvi, C. Thirumarai, Subramaninan, R. S. Sankara, Aparna, M., Dhanushree, V. M., Deepak, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Satheeskumaran, S., editor, Zhang, Yudong, editor, Balas, Valentina Emilia, editor, Hong, Tzung-pei, editor, and Pelusi, Danilo, editor

Published
2024
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15. Maritime Vessel Segmentation in Satellite Imagery Using UNET Architecture and Multiloss Optimization

Author

Ghadekar, Premanand, Deshpande, Mihir, Gharpure, Adwait, Gokhale, Vedant, Gore, Aayush, Yadav, Harsh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Satheeskumaran, S., editor, Zhang, Yudong, editor, Balas, Valentina Emilia, editor, Hong, Tzung-pei, editor, and Pelusi, Danilo, editor

Published
2024
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16. Prediction of Diabetic Retinopathy Using Deep Learning

Author

Harish, H., Bharathi, D. S., Pallavi, S., Shilpa, P., Elizabeth, S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Satheeskumaran, S., editor, Zhang, Yudong, editor, Balas, Valentina Emilia, editor, Hong, Tzung-pei, editor, and Pelusi, Danilo, editor

Published
2024
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17. Alzheimer’s Disease Detection Using Resnet

Author

Patel, Priyanka, Patil, Rohini, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Satheeskumaran, S., editor, Zhang, Yudong, editor, Balas, Valentina Emilia, editor, Hong, Tzung-pei, editor, and Pelusi, Danilo, editor

Published
2024
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18. Subject adaptation network for EEG data analysis.

Author

Ming, Yurui, Ding, Weiping, Pelusi, Danilo, Wu, Dongrui, Wang, Yu-Kai, Prasad, Mukesh, and Lin, Chin-Teng

Subjects
BRAIN-computer interfaces, DATA analysis, ELECTROENCEPHALOGRAPHY, SIGNAL processing, PHYSIOLOGICAL adaptation
Abstract

Biosignals tend to display manifest intra- and cross-subject variance, which generates numerous challenges for electroencephalograph (EEG) data analysis. For instance, in the context of classification, the discrepancy between EEG data can make the trained model generalising poorly for new test subjects. In this paper, a subject adaptation network (SAN) inspired by the generative adversarial network (GAN) to mitigate different variances is proposed for analysing EEG data. First the challenges faced by traditional approaches employed for EEG signal processing are emphasised. Then the problem is formulated from mathematical perspective to highlight the key points in resolving such discrepancies. Third, the motivation behind and design principle of the SAN are described in an intuitive manner to reflect its suitability for analysing EEG data. Then after depicting the overall architecture of the SAN, several experiments are used to justify the practicality and efficiency of using the proposed model from different perspectives. For instance, an EEG dataset captured during a stereotypical neurophysiological experiment called the VEP oddball task is utilised to demonstrate the performance improvement achieved by running the SAN. • A theoretical basis is formalised to guide the model design. • A subject adversarial network is proposed to mitigate EEG data variance. • Various experiments are provided to show the model's effectiveness. • Tricks from the implementation perspective are discussed. [ABSTRACT FROM AUTHOR]

Published
2019
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19. Analytical Comparison of Deep Learning Frameworks for Semantic Segmentation with Pixel-Level Understanding

Author

Deb, Ankit, Das, Shuvrajeet, Deb, Suman, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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20. A Comparative Study of Deep Learning-Based Face Recognition and Emotion Detection Techniques Using Social Media Customized Cartoon Post

Author

Paul, Jayanta, Roy, Anuska, Mallick, Siddhartha, Sil, Jaya, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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21. Identification of Diabetic Retinopathy Using Robust Segmentation Through Mask RCNN

Author

Aryan, Deb, Suman, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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22. Deep Convolutional Neural Network for Skin Cancer Classification

Author

Dash, Pandit Byomakesha, Kishore, Ch Ravi, Kommu, Venkatasai, Raju, Vysyaraju Lokesh, Mohapatra, Subhasree, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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23. An Improved Intrusion Detection System for the Internet of Medical Things Based on Deep Convolutional Neural Network

Author

Dash, Pandit Byomakesha, Behera, H. S., Senapati, Manas Ranjan, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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24. Detection and Classification of Dental Caries Using Deep and Transfer Learning

Author

Rajput, Divya, Rane, Hiral, Nikam, Devika, Wagh, Janhavi, Jadhav, Anuja, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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25. A Transfer Learning Approach to Indian Currency Coin Recognition

Author

Priyadharshini, R. Ahila, Vijayraj, M., Dhanushraj, R., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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26. Classifying Fetal Health Using Neural Networks by Boosting Imbalanced Classes

Author

Anoosha, Perumalla, Parlapalli, Renuka Devi, Srikanth Reddy, E., Menaga, P., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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27. A Deep Learning Approach for Detection of Disease in Plant Leaves

Author

Khatri, S., Tripathy, B. K., Kumar, K. V. S. S., Kumar, V., Bharti, S., Gupta, A., Khandelwal, Y., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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28. A CNN-Based Approach for Face Recognition Under Different Orientations

Author

Ahila Priyadharshini, R., Hariharan, S., Jagadeeswara, R., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2023
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30. Accident Detection in Surveillance Camera

Author

Adil, A. P., Anandhu, M. G., Joy, Jeovan Elsa, Karethara, Twinkle S., Anjali, S., Poorna, B. R., Xhafa, Fatos, Series Editor, Hemanth, Jude, editor, Pelusi, Danilo, editor, and Chen, Joy Iong-Zong, editor

Published
2023
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31. Statistical Analysis of Blockchain Models from a Cloud Deployment Standpoint

Author

Taiwade, Himanshu V., Ambhore, Premchand B., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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32. A Review on Fish Species Classification and Determination Using Machine Learning Algorithms

Author

Natarajan, Sowmya, Ponnusamy, Vijayakumar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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33. COVID-19 Detection Using X-Ray Images by Using Convolutional Neural Network

Author

Jany Shabu, S. L., Bharath Vinay Reddy, S., Satya Ranga Vara Prasad, R., Refonaa, J., Dhamodaran, S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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34. Text Summarization of Legal Documents Using Reinforcement Learning: A Study

Author

Shukla, Bharti, Gupta, Sonam, Yadav, Arun Kumar, Yadav, Divakar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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35. A Review of the Techniques and Evaluation Parameters for Recommendation Systems

Author

Vijaya Shetty, S., Dassani, Khush, Harish Gowda, G. P., Sarojadevi, H., Hariprasad Reddy, P., Singh, Sehaj Jot, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Raj, Jennifer S., editor, Shi, Yong, editor, Pelusi, Danilo, editor, and Balas, Valentina Emilia, editor

Published
2022
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36. Deep Learning Based Framework for Breast Cancer Mammography Classification Using Resnet50

Author

Dash, Pandit Byomakesha, Behera, H. S., Senapati, Manas Ranjan, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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37. Deep Learning Based Facial Mask Detection Using Mobilenetv2

Author

Goswami, Arijit, Bhattacharjee, Biswarup, Debnath, Rahul, Sikder, Ankita, Basu Pal, Sudipta, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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38. Deep Learning Approach for Anamoly Detection in CAN Bus Network: An Intelligent LSTM-Based Intrusion Detection System

Author

Kishore, Ch. Ravi, Rao, D. Chandrasekhar, Behera, H. S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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39. Low-Computation IoT System Framework for Face Recognition Using Deep Learning Algorithm

Author

Paul, Jayanta, Bhowmick, Rajat Subhra, Sil, Jaya, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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40. A Proposed Federated Learning Model for Vaccination Tweets

Author

Singh, Medha, Madhulika, Bansal, Shefali, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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41. Deep Learning Based Identification of Three Exotic Carps

Author

Banerjee, Arnab, Chakraborty, Roopsia, Behra, Samarendra, Srinivasan, Nagesh Talagunda, Bhattacharjee, Debotosh, Das, Nibaran, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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42. A Deep Learning Based Approach to Measure Confidence for Virtual Interviews

Author

Rungta, Ravi Kumar, Jaiswal, Parth, Tripathy, B. K., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
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43. Deep Features for COVID-19 Detection: Performance Evaluation on Multiple Classifiers

Author

Lasker, Asifuzzaman, Ghosh, Mridul, Obaidullah, Sk Md, Chakraborty, Chandan, Roy, Kaushik, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
Full Text
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44. Image Splicing Detection Using Feature Based Machine Learning Methods and Deep Learning Mechanisms

Author

Das, Debjit, Naskar, Ruchira, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
Full Text
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45. TextUnet: Text Segmentation Using U-net

Author

Banerjee, Awritrojit, Ghoshal, Ranjit, Ghosal, Arijit, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Asit Kumar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, Vimal, S., editor, and Pelusi, Danilo, editor

Published
2022
Full Text
View/download PDF

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