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).

 

Chapter 1. Revolutions in Infant fingerprint Recognition-A Survey.- Chapter 2. A Review of High Utility Itemset Mining for Transactional Database.- Chapter 3. A Cross-sectional study on distributed mutual exclusion algorithms for ad hoc networks.- Chapter 4. Electromagnetic Pollution Index Estimation of Green Mobile Communication of Macrocell.- Chapter 5. Prediction of Train delay System in Indian Railways using Machine Learning Techniques: Survey.- Chapter 6. Valence of emotion recognition using EEG.- Chapter 7. A Deep Learning-based Approach for Automated Brain Tumor Segmentation in MR images.- Chapter 8. MZI based Electro-Optic Reversible XNOR/XOR Derived from Modified Fredkin Gate.- Chapter 9. Secured Remote Access of Cloud Based Learning Management System (LMS) Using VPN.- Chapter 10. Surface EMG signal classification for hand gesture recognition.- Chapter 11. Improved Energy Efficiency in Street Lighting: A Coverage based Approach.- Chapter 12. Security and Challenges for Cognitive IOT Based Future City Architecture.- Chapter 13. A Heuristic Model for Friend Selection in Social Internet of Things.- Chapter 14. A Fuzzy string matching based reduplication with morphological attributes.- Chapter 15. Accelerating LOF Outlier Detection Approach. etc.

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 Sof