Deep Learning Applications, Volume 4 (eBook)

This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.

Dr. M. Arif Wani is currently a Professor at the University of Kashmir, having previously served as a Professor at California State University Bakersfield. He completed his M. Tech. in Computer Technology at the   Indian Institute of Technology, Delhi, and his Ph.D. in Computer Vision at Cardiff University, UK. His research interests are in the area of machine learning, with a focus on neural networks, deep learning, inductive learning, and support vector machines, and with application to areas that include computer vision, pattern recognition, classification, prediction and analysis of gene expression datasets. He has published many papers in reputed journals and conferences in these areas. Dr. Wani has co-authored the book 'Advances in Deep Learning', co-edited many books in 'Machine Learning and Applications' and 'Deep Learning Applications'. He is a member of many academic and professional bodies.

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This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.