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Your search keyword '"Nijalingappa, Pradeep"' showing total 6 results
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6 results on '"Nijalingappa, Pradeep"'

1. Machine Learning Techniques for Human Age and Gender Identification Based on Teeth X-Ray Images

Author

K. C. Santosh, Nijalingappa Pradeep, Vikas Goel, Raju Ranjan, Ekta Pandey, Piyush Kumar Shukla, and Stephen Jeswinde Nuagah

Subjects
Medicine (General), Article Subject, X-Rays, Biomedical Engineering, India, Health Informatics, Machine Learning, R5-920, Radiography, Panoramic, Medical technology, Humans, Surgery, R855-855.5, Tooth, Biotechnology, Research Article
Abstract

The use of digital medical images is increasing with advanced computational power that has immensely contributed to developing more sophisticated machine learning techniques. Determination of age and gender of individuals was manually performed by forensic experts by their professional skills, which may take a few days to generate results. A fully automated system was developed that identifies the gender of humans and age based on digital images of teeth. Since teeth are a strong and unique part of the human body that exhibits least subject to risk in natural structure and remains unchanged for a longer duration, the process of identification of gender- and age-related information from human beings is systematically carried out by analyzing OPG (orthopantomogram) images. A total of 1142 digital X-ray images of teeth were obtained from dental colleges from the population of the middle-east part of Karnataka state in India. 80% of the digital images were considered for training purposes, and the remaining 20% of teeth images were for the testing cases. The proposed gender and age determination system finds its application widely in the forensic field to predict results quickly and accurately. The prediction system was carried out using Multiclass SVM (MSVM) classifier algorithm for age estimation and LIBSVM classifier for gender prediction, and 96% of accuracy was achieved from the system.

Published
2022

4. Advances in Explainable AI Applications for Smart Cities

Author

Mangesh M. Ghonge, Nijalingappa Pradeep, Noor Zaman Jhanjhi, Praveen M. Kulkarni, Mangesh M. Ghonge, Nijalingappa Pradeep, Noor Zaman Jhanjhi, and Praveen M. Kulkarni

Subjects
Artificial intelligence, Smart cities, Human-computer interaction
Abstract

'This book is an essential resource for undergraduate and postgraduate students, researchers, academicians, industry professionals, and scientists working in research laboratories. It provides a comprehensive overview of XAI concepts, advantages over AI, and its applications in smart city development. By showcasing the impact of XAI on various smart city applications, the book enables readers to understand the importance of XAI in creating more sustainable and efficient smart cities. Additionally, the book addresses the open challenges and research issues related to XAI in modern smart cities, providing a roadmap for future research in this field. Overall, this book is a valuable resource for anyone interested in understanding the importance of XAI in smart city applications'--

Published
2024

5. Utilizing Blockchain Technologies in Manufacturing and Logistics Management

Author

S. B. Goyal, Nijalingappa Pradeep, Piyush Kumar Shukla, Mangesh M. Ghonge, Renjith V. Ravi, S. B. Goyal, Nijalingappa Pradeep, Piyush Kumar Shukla, Mangesh M. Ghonge, and Renjith V. Ravi

Subjects
Industrial management--Technological innovations, Manufacturing industries--Technological innovations, Blockchains (Databases)
Abstract

Blockchain technology has the potential to utterly transform supply chains, streamline processes, and improve the whole of security. Manufacturers across the globe face challenges with forecasting demand, controlling inventory, and accelerating digital transformation to cater to the challenges of changing market dynamics and evolving customer expectations. Hence, blockchain should be seen as an investment in future-readiness and customer-centricity, not as an experimental technology. Utilizing Blockchain Technologies in Manufacturing and Logistics Management explores the strengths of blockchain adaptation in manufacturing industries and logistics management, which include product traceability, supply chain transparency, compliance monitoring, and auditability, and also examines the current open issues and future research trends of blockchain. Leveraging blockchain technology into a manufacturing enterprise can enhance its security and reduce the rates of systematic failures. Covering topics such as fraud detection, Industry 4.0, and security threats, this book is a ready premier reference for graduate and post-graduate students, academicians, researchers, industrialists, consultants, and entrepreneurs, as well as micro, small, and medium enterprises.

Published
2022

6. Demystifying big data, machine learning, and deep learning for healthcare analytics / edited by Pradeep Nijalingappa, Sandeep Kautish, Sheng Lung Peng.

Author

Nijalingappa, Pradeep, Kautish, Sandeep, and Peng, Sheng Lung

Subjects
Medical informatics, Machine learning, Big data
Abstract

Summary: "Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians"-- Provided by publisher.

Published
2021

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