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Advanced Techniques for IoT Applications: Proceedings of EAIT 2020 1st ed. 2022 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 617 pages, height x width: 235x155 mm, weight: 955 g, 243 Illustrations, color; 139 Illustrations, black and white; XIV, 617 p. 382 illus., 243 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Networks and Systems 292
  • Izdošanas datums: 03-Aug-2021
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9811644349
  • ISBN-13: 9789811644344
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  • Formāts: Paperback / softback, 617 pages, height x width: 235x155 mm, weight: 955 g, 243 Illustrations, color; 139 Illustrations, black and white; XIV, 617 p. 382 illus., 243 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Networks and Systems 292
  • Izdošanas datums: 03-Aug-2021
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9811644349
  • ISBN-13: 9789811644344
Citas grāmatas par šo tēmu:

This book includes original, unpublished contributions presented at the Sixth International Conference on Emerging Applications of Information Technology (EAIT 2020), held at the University of Kalyani, Kalyani, West Bengal, India, on November 2020. The book covers the topics such as image processing, computer vision, pattern recognition, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks, and IoT. It will also include IoT application-related papers in pattern recognition, artificial intelligence, expert systems, natural language understanding, image processing, computer vision, applications in biomedical engineering, artificial neural networks, fuzzy logic, evolutionary optimization, data mining, Web intelligence, intelligent agent technology, virtual reality, and visualization.

Part I: Image Processing, Computer Vision and Pattern Recognition.-
Genetic Dropout: An application to Handwritten Indic Script Classification.-
Encryption of Optically Compressed Medical Images using Phase Matrix.-
Application of image processing for reconstruction of PATHA art, a cultural
heritage of eastern India: An approach using particle swarm optimization
technique.- A Transfer learning-based approach for lung inflammation
detection.- Caption bot for Assistive Vision.- Tiny Vessels Exploration in
Retinal Image using BFS Influenced Flood Filling.- A Reliable and Fast
Detection Technique for Lung Cancer Using Digital Image Processing.-
Correlation based cluster validity index for recognition of Leukemia
mediating biomarkers.- An Approach for Ultrasound Image Enhancement Using
Deep Convolutional Neural Network.- Food Calorie Estimation System Using
Image ai with Retinanet Feature Extraction.- Sketch-based Image Retrieval
using Convolutional Neural Networks based on Feature Adaptation and Relevance
Feedback.- Dual image-based data hiding scheme using Quorum Function.- Part
II: Intelligent information systems.- Pathway Marker Identification Using
Gene Expression Data Analysis: A Particle Swarm Optimisation Approach.-
Forecasting of the WPI of Textiles in India: An Neural Approach.- Determining
Dark Diversity of Different Faunal Groups in Indian Estuarine Ecosystem: A
New Approach with Computational Biodiversity.
Professor J.K. Mandal received his M.Sc. in Physics from Jadavpur University in 1986 and M.Tech. in Computer Science from the University of Calcutta and was awarded a Ph.D. in Computer Science and Engineering by Jadavpur University in 2000. Currently, he is Professor of Computer Science and Engineering and was Dean of the Faculty of Engineering, Technology, and Management, Kalyani University, West Bengal, for two consecutive terms. He started his career as Lecturer at NERIST, Arunachal Pradesh, in September 1988 and has 30 years of teaching and research experience. His research areas include coding theory, data and network security, remote sensing and GIS-based applications, data compression, error correction, visual cryptography, steganography, security in MANET, wireless networks, and unified computing. He has been Life Member of the Computer Society of India since 1992, CRSI since 2009, ACM since 2012, IEEE since 2013 and Fellow of IETE since 2012. He has chaired more than 60 sessions at various international conferences and delivered more than 60 experts/invited lectures during the last 5 years. He has acted Program Chair of several international conferences and edited more than 30 proceedings volumes. He is Reviewer for various international journals and conferences and has published over 360 articles. He is one of the editors for the Springer AISC and CCIS Series. He has published more than 450 articles, out of which 160 papers are published in the international journal. He has authored 12 books. Twenty-four scholars were awarded Ph.D. degrees under his supervision.





 





Professor Debashis De is Director of the School of Computational Science and Professor Department of Computer Science and Engineering, of the Maulana Abul Kalam Azad University of Technology, West Bengal, India. He is Adjunct Research Fellow at the University of Western Australia, Australia. The Department of Science and Technology awarded him the prestigious Boys cast Fellowship, Government of India, to work at the Herriot-Watt University, Scotland, UK. He received the Endeavour Fellowship Award from 20082009 by DEST Australia to work at the University of Western Australia, Perth. He received the Young Scientist Award both in 2005 at New Delhi and in 2011 in Istanbul, Turkey, from the International Union of Radio Science, Belgium. In 2016, he received the JC Bose Research Award by IETE, New Delhi. In 2019, he received Siksha Ranta Award by the Government of West Bengal. He was listed in top 2% scientist list of the world, Stanford University, USA. He is serving as Vice-Chair of IEEE DEW Computing STC, Senior Member of IEEE, and Fellow of IETE. His research interests include mobile edge computing and IoT. He published more than 300 peer-reviewed journals and 100 conference papers, nine filed patents, eight research monographs in CRC, Springer, NOVA, Elsevier, and five textbooks in Pearson. His h index is 31, citation 4500.