Bio-inspired Neurocomputing -

Bio-inspired Neurocomputing

Buch | Softcover
427 Seiten
2021 | 1st ed. 2021
Springer Verlag, Singapore
978-981-15-5497-1 (ISBN)
192,59 inkl. MwSt
This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchersas well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.

Dr. Akash Kumar Bhoi [PhD (Sikkim Manipal University), M.Tech (Karunya University), B.Tech (TAT, BPUT)] working as Assistant Professor in the Department of Electrical and Electronics Engineering at Sikkim Manipal Institute of Technology (SMIT), SMU, India. He has specialized in the field of Biomedical Engineering.  His areas of research are biomedical signal processing, Medical Image Processing, Computational Approaches and Pattern Recognition etc.. He is also a regular reviewer of journals of repute namely IEEE, Springer, Elsevier, Taylor and Francis, Inderscience etc. He has published several papers in national and international journals and conferences. He has also served on numerous organizing panels for the international conferences and workshops. He is currently editing several books with Springer Nature and serving as Guest editor for special issues of the journal like Springer Nature and Inderscience. Dr. Pradeep Kumar Mallick is currently working as Associate Professor in the School of Computer Engineering, Kalinga Institute of Industrial technology (KIIT) Deemed to be University, Odisha, India. He was a postdoctoral fellow in Kongju National University South Korea. He received his PhD from Siksha O Anusandhan University, M.Tech. (CSE) from Biju Patnaik University of Technology (BPUT), and MCA from Fakir Mohan University Balasore, India. Besides academics, he is also involved in various administrative activities - he is a Member of Board of Studies, Member of Doctoral Research Evaluation Committee, and Admission Committee. His areas of research include algorithm design and analysis, data mining, image processing, soft computing, and machine learning. He has published 5 books and more than 55 research papers in national and international journals and conference proceedings. Dr. Chuan-Ming Liu is a professor in the Department of Computer Science and Information Engineering (CSIE), National Taipei University of Technology (Taipei Tech), TAIWAN, where he was the Department Chair from 2013-2017. Currently, he is pointed to be the Head of the Extension Education Center at the same school. Dr. Liu received his Ph.D. in Computer Science from Purdue University in 2002 and joined the CSIE Department in Taipei Tech in the spring of 2003. In 2010 and 2011, he has held visiting appointments with Auburn University, Auburn, AL, USA, and the Beijing Institute of Technology, Beijing, China. He has services in many journals, conferences and societies as well as published more than 100 papers in many prestigious journals and international conferences. Dr. Liu was the co-recipients of many conference best paper awards, including ICUFN 2015 Excellent Paper Award, ICS 2016 Outstanding Paper Award, and WOCC 2018 Best Paper Award. His current research interests include big data management and processing, uncertain data management, data science, spatial data processing, data streams, ad-hoc and sensor networks, location-based services. Dr. Valentina Emilia Balas is currently Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad , Romania. She holds a Ph.D. in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 300 research papers in refereed journals and international conferences. Her research interests include intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling and simulation. She is the Editor-in Chief of the International Journal of Advanced Intelligence Paradigms and the International Journal of Computational Systems Engineering. She also serves as an editorial board member of several national and international journals and is the Director of the Department of International Relations and Head of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad. She is a member of EUSFLAT, SIAM and a Senior Member IEEE, member in TC–Fuzzy Systems (IEEE CIS), chair of the TF 14 in TC – Emergent Technologies (IEEE CIS), member in TC – Soft Computing (IEEE SMCS).  

Performance Measurement of various Hybridized kernels for Noise Normalization.- A precise analysis of Deep Learning for Medical Image Processing.- Artificial Intelligence for Internet of Things.- A Brief Review on Brain Tumour Detection.- Deep Learning Techniques for Electronic Health.- A Review on Psychological Brainwaves Behavior.

Erscheinungsdatum
Reihe/Serie Studies in Computational Intelligence ; 903
Zusatzinfo 111 Illustrations, color; 48 Illustrations, black and white; XII, 427 p. 159 illus., 111 illus. in color.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
Naturwissenschaften Biologie Humanbiologie
Naturwissenschaften Biologie Zoologie
Technik
Schlagworte Bio-computational Learning Theory • brain inspired computing • Computational Models for Neuroscience • Deep Learning Biomedical Imaging • Genetic Algorithms in Medical Diagnosis • Machine Learning in Bio-signals and Bio-imaging • Neurobiology and Pattern Recognition
ISBN-10 981-15-5497-8 / 9811554978
ISBN-13 978-981-15-5497-1 / 9789811554971
Zustand Neuware
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