Machine Vision and Augmented Intelligence

Select Proceedings of MAI 2022

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Springer


Paru le : 2023-04-30



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Description
This book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2022). The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the book. The book encompasses all industrial and non-industrial applications. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, image processing, and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in health care, brain-computer interface, cybersecurity, social network analysis, and natural language processing.?
Pages
663 pages
Collection
n.c
Parution
2023-04-30
Marque
Springer
EAN papier
9789819901883
EAN PDF
9789819901890

Informations sur l'ebook
Nombre pages copiables
6
Nombre pages imprimables
66
Taille du fichier
24771 Ko
Prix
232,09 €
EAN EPUB
9789819901890

Informations sur l'ebook
Nombre pages copiables
6
Nombre pages imprimables
66
Taille du fichier
139776 Ko
Prix
232,09 €

Koushlendra Kumar Singh is currently working as an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology, Jamshedpur, India. He completed his doctoral degree and master’s program at the Indian Institute of Information Technology, Design, and Manufacturing, Jabalpur, India, in 2016 and 2011, respectively. Dr. Singh graduated in computer science and engineering from Bhagalpur College of Engineering, Bhagalpur, in 2008. He has published several papers in international refereed journals and conferences. His current research interest areas are image processing, biometrics, different applications of fractional derivatives, computational modeling, epidemic forecasting, etc.

Manish Kumar Bajpai is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Information Technology Design and Manufacturing, Jabalpur, India. He completed his Ph.D. from IIT Kanpur in image reconstruction and parallel algorithm design. Dr. Bajpai has published over 50 publications in international journals and conferences. He has several sponsored research and consultancy projects funded by agencies such as SPARC, MHRD, DST, USIEF, ATAL, BRNS, and NVIDIA. Eleven students have completed/pursuing their Ph.D. under his supervision. His research areas are augmented intelligence, machine vision, brain-computer interface, medical imaging, and parallel algorithms design. Dr. Bajpai is a senior member of IEEE and a life member of the Indian Science Congress and Indian Nuclear Society.

Dr. Akbar Sheikh Akbari is an associate professor (Reader) of Electronic Engineering in the School of Built Environment, Engineering and Computing. He has a B.Sc. (Hons), M.Sc. (distinction), and Ph.D. in Electronic and Electrical Engineering. After completing his Ph.D. at Strathclyde University, he joined Bristol University to work on an EPSRC project in stereo/multi-viewvideo processing. Dr. Sheikh Akbari’s main areas of research are: biometric identi?cation techniques, e.g., iris, ear, and face recognition, image resolution enhancement (super-resolution) methods, image source camera identi?cation, color constancy (white balancing) techniques, standard and non-standard image/video codecs, e.g., H.264 and HEVC, multi-view image/video processing, video analytics and real-time embedded systems, edge detection in low SNR environments, compressive sensing, retro-re?ective materials, online camera calibration. Dr. Sheikh Akbari was the academic supervisor for the following KTP project: Omega Security Systems/Leeds Beckett University, “Research, develop and implement a scalable and modular system which monitors and analyses individual behavioural patterns and movements in a range of environments”, Funder: innovate UK, 24 months, £122,040, which was graded outstanding by innovate UK.

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