This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from Io T devices, smart systems, speech, and videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves a valuable resource for those in academia and industry.
Table of Content
On Diverse and Serendipitous item Recommendation: A Reinforced Similarity and Multi-Objective Optimization based Composite Recommendation Framework.- Comparative Analysis of Node Dependent and Node Independent Graph Matrices for Brain Connectivity.- Facial Expression Recognition from low resolution facial segments using Pre-trained networks.- Design and Analysis of Quad Element UWB MIMO Antenna with Mutual Coupling Reduction Techniques.- Enhancing Agriculture Outcome with Multiple Crop Recommendations Using Sequential Forword Feature Selection.- Kernel Level Pruning for CNN.
About the author
Dilip Singh Sisodia is an Associate Professor and Head at the Department of Computer Science Engineering of National Institute of Technology Raipur. Dr. Sisodia contributed over 100 high-impact articles in reputed journals, conference proceedings, and edited volumes. He also edited Scopus indexed research book volumes published by Springer Nature and IGI Global. Dr. Sisodia was included in the World Ranking of Top 2% Scientists/researchers in 2022 by a study of Scientists from Stanford University USA and Published by Elsevier B.V. So far he has supervised four Ph.D. thesis, eight M.Tech. dissertations and more than 50 B.Tech. projects. He is a Senior Member of IEEE and ACM. He received a Ph.D. degree in computer science and engineering from the National Institute of Technology Raipur, India. He earned his M.Tech. and B.E. degrees, respectively, in information technology (with specialization in artificial intelligence) and computer science and engineering from the Rajiv Gandhi Technological University, Bhopal, India. His research interests include the applications of machine learning/soft computing techniques, artificial intelligence, biomedical signal, and image processing.
Lalit Garg is a Senior Lecturer in the Department of Computer Information Systems at the University of Malta, Malta, and an Honorary Lecturer at the University of Liverpool, UK. He has been a Researcher at the Nanyang Technological University, Singapore, and Ulster University, UK, has supervised 200+ Master’s dissertations, two DBA, and two Ph.D. theses, and published 120+ high-impact publications in refereed journals/conferences/books, five edited books, and 20 patents. His research interests are business intelligence, machine learning, data science, deep learning, cloud computing, mobile computing, the Internet of Things (Io T), information systems, management science, and their applications mainly in healthcare and medical domains.
Ram Bilas Pachori received a B.E. degree with honors in Electronics and Communication Engineering from Rajiv Gandhi Technological University, Bhopal, India, in 2001, the M.Tech. and Ph.D. degrees in Electrical Engineering from Indian Institute of Technology (IIT) Kanpur, Kanpur, India, in 2003 and 2008, respectively. He was Postdoctoral Fellowship Holder at Charles Delaunay Institute, the University of Technology of Troyes, Troyes, France, from 2007 to 2008. He is a Professor in the Department of Electrical Engineering at IIT Indore, India. His research interests are in the areas of signal and image processing, biomedical signal processing, non-stationary signal processing, speech signal processing, brain-computer interfacing, machine learning, and artificial intelligence in health care. He has supervised 14 Ph.D., 20 M.Tech., and 41 B.Tech. students for their theses and projects. He has over 235 publications which include journal papers, conference papers, books, and chapters. He has worked on various research projects with fundingsupport from SERB, DST, DBT, and CSIR.
M. Tanveer is an Associate Professor and Ramanujan Fellow at the Discipline of Mathematics of the Indian Institute of Technology Indore. Prior to that, he worked as Postdoctoral Research Fellow at the Rolls-Royce@NTU Corporate Lab of the Nanyang Technological University, Singapore. He received a Ph.D. degree in Computer Science from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, optimization, machine learning, deep learning, and applications to Alzheimer’s disease and dementia. He has published over 80 research papers in journals of international repute.
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