Pattern Recognition and Data Analysis with Applications

This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multi-task, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG) and electromyogram (EMG).

Dr. Deepak Gupta is Assistant Professor at the Department of Computer Science & Engineering of National Institute of Technology Arunachal Pradesh. He received the Ph.D. degree in Computer Science & Engineering from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, ELM, RVFL, KRR and other machine learning techniques. He has published over 40 referred journal and conference papers of international repute. His publications have around 372 citations with an h-index of 12 and i10-index of 12 (Google Scholar, 26/02/2021). He is the recipient of the 2017 SERB-Early Career Research Award in Engineering Sciences which is the prestigious award of INDIA at early career level. He is a senior member of IEEE and currently an active member of many scientific societies like IEEE, SMC, CIS, CSI and many more. He is currently the member of an editorial review board member of Applied Intelligence. He has also served as a reviewer of many scientific journals and various national and international conferences. He is currently Principal Investigator (PI) or Co-PI of 02 major research projects funded by the Science & Engineering Research Board (SERB), Government of India.  

Dr. Rajat Subhra Goswami received his B.Tech. in Information Technology in 2005 from West Bengal University of Technology, West Bengal. He received his M.E. in Multimedia Development from Jadavpur University, West Bengal, in 2009 and then joined in Bengal Institute of Technology Shantiniketan, Bolpur, West Bengal, as Assistant Professor in CSE department. He became Assistant Professor of CSE department at National Institute of Technology, Arunachal Pradesh, Govt. of India, in 2011. He received Ph,D, in Computer Science & Engineering from National Institute of Technology Arunachal Pradesh in 2015. Currently, he is working as Assistant Professor in the department of Computer Science and Engineering in National Institute of Technology, Arunachal Pradesh, Govt. of India. He has more than 10 years of experience as a teacher. Cryptography, big data and machine learning are his research areas. In separate national/international journals/conferences, he has written over 50 research papers. Two Ph.D. scholars were awarded under his supervision, and four scholars are now working in separate fields. He is a life member of Indian Science Congress Association and Cryptology Research Society of India. 

Dr. Subhasish Banerjee received his Ph.D. in Computer Science and Engineering from National Institute of Technology, Arunachal Pradesh, in 2016 and M.Tech. degree in Computer Application from Indian Institute of Technology (ISM), Dhanbad, India, in 2012. Currently, he is working as Assistant Professor in the Department of Computer Science and Engineering in National Institute of Technology, Arunachal Pradesh. His research activities are mainly focused on cryptography, networking and information security. He is the author or co-author of more than 20 papers in international refereed journals and more than 20 paper contributions in referred international conference.

Dr. M. Tanveer is Associate Professor and Ramanujan Fellow at the Discipline of Mathematics of the Indian Institute of Technology Indore. Prior to that, he spent one year as a Postdoctoral Research Fellow at the Rolls-Royce@NTU Corporate Lab of the Nanyang Technological University, Singapore. During 2012 to 2015, he was Assistant Professor at the Department of Computer Science and Engineering of the LNM Institute of Information Technology (LNMIIT), Jaipur. He received the Ph.D. degree in Computer Science from the Jawaharlal Nehru University, New Delhi, India. Prior to that, he received the M.Phil. degree in Mathematics from Aligarh Muslim University, Aligarh, India. His research interests include support vector machines, optimization, machine learning, deep learning, applications to Alzheimer's disease and dementias, biomedical signal processing and fixed point theory and applications. He has published over 50 referred journal papers of international repute. His publications have around 1100 citations with h index 21 (Google Scholar, January 2021). Recently, he has been listed in the world's top 2% scientists in the study carried out by Stanford University, USA. He has served on review boards for more than 100 scientific journals and served for scientific committees of various national and international conferences. He is the recipient of the 2017 SERB-Early Career Research Award in Engineering Sciences and the only recipient of 2016 DST-Ramanujan Fellowship in Mathematical Sciences which are the prestigious awards of INDIA at early career level. He is currently the member of Editorial Board/Guest Editor/Associate Editor in several journals including ACM Transactions of Multimedia (TOMM), Applied Soft Computing, Elsevier, IEEE Transactions on Emerging Topics in Computational Intelligence, Frontiers in Applied Mathematics and Statistics, Applied Intelligence, Springer, Multimedia Tools and Applications, Springer and Smart Science, Taylor & Francis. He has also co-edited one book in Springer on machine intelligence and signal analysis. He has organized many international/national conferences/symposium/workshop as General Chair/Organizing Chair/Coordinator and delivered talks as Keynote/Plenary/invited speaker in many international conferences and Symposiums. He has organized several special sessions in top-ranked conferences including WCCI, IJCNN, IEEE SMC, IEEE SSCI, ICONIP. Amongst other distinguished, international conference chairing roles, he is the General Chair for 29th International Conference on Neural Information Processing (ICONIP2022) (the world's largest and top technical event in Computational Intelligence). He is currently Principal Investigator (PI) or Co-PI of 07 major research projects funded by Government of India including Department of Science and Technology (DST), Science & Engineering Research Board (SERB) and Council of Scientific & Industrial Research (CSIR), MHRD-SPARC.

Prof. Ram Bilas Pachori received the B.E. degree with honours 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 worked as Postdoctoral Fellow at Charles Delaunay Institute, University of Technology of Troyes, Troyes, France, during 2007–2008. He served as Assistant Professor at Communication Research Center, International Institute of Information Technology, Hyderabad, India, during 2008–2009. He served as Assistant Professor at Department of Electrical Engineering, IIT Indore, Indore, India, during 2009–2013. He worked as Associate Professor at Department of Electrical Engineering, IIT Indore, Indore, India, during 2013–2017 where presently he has been working as Professor since 2017. He is also Associated Faculty with Department of Biosciences & Biomedical Engineering and Center for Advanced Electronics at IIT Indore. He was Visiting Professor at School of Medicine, Faculty of Health and Medical Sciences, Taylor´s University, Subang Jaya, Malaysia, during 2018–2019. He worked as Visiting Scholar at Intelligent Systems Research Center, Ulster University, Northern Ireland, UK, during December 2014. He is Associate Editor of Electronics Letters, Biomedical Signal Processing and Control journal and Editor of IETE Technical Review Journal. He is Senior Member of IEEE and Fellow of IETE and IET. He has supervised 12 Ph.D., 20 M.Tech. and 37 B.Tech. students for their theses and projects. He has more than 210 publications which include journal papers (126), conference papers (66), books (04) and book chapters (16). His publications have around 7500 citations with h index of 46 (Google Scholar, January 2021). He has been listed in the top h index scientists in the area of computer science and electronics by Guide2Research website. He has been listed in the world’s top 2% scientists in the study carried out at Stanford University, USA. He has served on review boards for more than 100 scientific journals and served for scientific committees of various national and international conferences. He has delivered more than 135 talks in various conferences, workshops, short term courses and institutes. 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.