Machine Vision and Augmented Intelligence: Select Proceedings of MAI 2022 (Lecture Notes in Electrical Engineering, 1007)

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.

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 identification techniques, e.g., iris, ear, and face recognition, image resolution enhancement (super-resolution) methods, image source camera identification, 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-reflective 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.