Recent Advances in Deep Learning Applications : New Techniques and Practical Examples

This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers.

Key Features:

• Presents state-of-the-art research on deep learning
• Covers modern real-world applications of deep learning
• Provides value to students, academic researchers, professionals, software engineers in the industry, and innovative product developers

Dr. Uche Onyekpe is a Machine Learning Expert at Ofcom (Office of Communications, UK), where he focuses on developing assessment/audit strategies for AI algorithms used by online platforms such as Instagram, TikTok, and X. He also serves as the Director of the African Institute for Artificial Intelligence, a nonprofit organization dedicated to advancing AI across the African continent.

Dr. Onyekpe previously held academic positions at York St John University and Coventry University on Machine Learning. His professional experience spans various sectors, including health, construction, and transport, where he has led projects at the intersection of artificial intelligence and these fields. He has published numerous research papers in these areas and has several years of experience working as a consultant within the robotics and social care. He has delivered keynote talks at reputable seminars and events on machine learning and applications.

Vasile Palade is a Professor of Artificial Intelligence and Data Science in the Centre for Computational Science and Mathematical Modelling at Coventry University, UK. He previously held several academic and research positions at the University of Oxford - UK, University of Hull - UK, and the University of Galati - Romania. His research interests are in machine learning, with a focus on neural networks and deep learning, and with main application to computer vision, natural language processing, autonomous driving, smart cities, health, among others. Prof. Palade is author and co-author of more than 300 papers in journals and conference proceedings as well as several books on machine learning and applications. He is an Associate Editor for several reputed journals, such as IEEE Transactions on Neural Networks and Learning Systems, and Neural Networks. He has delivered keynote talks to reputed international conferences on machine learning and applications.

Prof. M. Arif Wani completed his M.Tech. in Computer Technology at the Indian Institute of Technology, Delhi, and his PhD in Computer Vision at Cardiff University, UK. He is a Professor at the University of Kashmir, having previously served as a Professor at California State University Bakersfield.

His research interests are in the area of machine learning, with a focus on neural networks, deep learning, computer vision, pattern recognition, and classification tasks. He has published many papers in reputed journals and conferences in these areas. Dr. Wani has co-authored the book ‘Advances in Deep Learning’ and co-edited many books on Machine Learning and Deep Learning applications.