R. Jagadeesh Kannan & Sabu M. Thampi 
Computer Vision and Machine Intelligence Paradigms for SDGs [PDF ebook] 
Select Proceedings of ICRTAC-CVMIP 2021

PTZ-camera-based facial expression analysis using faster R-CNN for student engagement recognition.- Convergence Perceptual Model for Computing Time-Series-Data on Fog-Environment.- Localized Super Resolution for Foreground Images using U-Net and MR-CNN.- SMS Spam Classification Using PSO-C4.5.- Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN.- Pest Detection using Improvised YOLO Architecture.- Classification of Fungi Effected Psidium Guajava Leaves using ML and DL Techniques.- Deep Learning Based Recognition of Plant Diseases.- Artificial Cognition of Temporal Events using Recurrent Point Process Networks.- On the Performance of Energy Efficient Video Transmission over LEACH based protocol in WSN.- Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Wordlevel.- Advanced Algorithmic Techniques for Topic Prediction and Recommendation – An Analysis.- Implementation of an automatic EEG feature extraction with Gated Recurrent Neural Network for Emotion Recognition.

R. Jagadeesh Kannan is a Professor in the School of Computer Science and Engineering at Vellore Institute of Technology, India. He completed his Ph.D. in Handwritten Character Recognition using Hybrid Techniques from Anna University, Chennai, India. He got his M.E. degree in Computer Science and Engineering from National Engineering College, Tamil Nadu, and B.E. in Instrumentation and Control Engineering from Madurai Kamaraj University, Tamil Nadu, India. Prof. Kannan has over 18 years of teaching and industrial experience in reputed organizations. Prof. Kannan has got several publications in conference proceedings and journals of national and international repute. His research interests are neural networks, fuzzy logic, neuro-fuzzy systems, soft computing tools, pattern recognition, natural language processing, image processing, networking, printed, handwritten and cursive character recognition, and artificial intelligence.

Sabu M. Thampi is a Professor atthe School of Computer Science and Engineering (So CSE), Kerala University of Digital Sciences, Innovation and Technology (KUDSIT) – formerly IIITM-K, Technocity Campus, Trivandrum, Kerala, India. He holds a Ph.D. in Computer Engineering from the National Institute of Technology Karnataka. His current research interests include the Internet of things (Io T), cognitive security, social networks, endpoint security, and smart cyber-physical systems. Sabu is also coordinating the Connected Systems and Intelligence (CSI) Lab at KUDSIT. Dr. Sabu has been actively involved in funded research projects and published papers in book chapters, journals, and conference proceedings. He has authored and edited a few books, as well as edited 45+ conference proceedings published by Springer in various series, as well as a few others published by IEEE, ACM, and Elsevier. Sabu has served as Guest Editor for special issues in a few journals and a program committee member for many international conferencesand workshops. He has co-chaired several international workshops and conferences. He has initiated (ISTA, SSCC, SIRS, ISI, So MMA, ACN, and Co Co Net…) and is also involved in the organization of several annual conferences/symposiums. Sabu is currently serving as Editor for Elsevier Journal of Network and Computer Applications (JNCA), Elsevier Journal of Engineering Applications of Artificial Intelligence (2022), Connection Science – Taylor & Francis; Associate Editor for IEEE Access and International Journal of Embedded Systems, Inderscience, UK; and Reviewer for several reputed international journals. Sabu is a Senior Member of IEEE and ACM. He is the Founding Chair of the ACM Trivandrum Professional Chapter.

Shyh-Hau Wang is a Professor in the Department of Computer Science and Information Engineering (CSIE); Institute of Medical Informatics (IMI); MS Program in Artificial Intelligence Technology at National Cheng Kung University (NCKU), Tainan, Taiwan. He completed his Ph.D. in Bioengineering at the Pennsylvania State University (PSU), USA. His research interests include medical and healthcare informatics, ultrasound signal and imaging system, machine/deep learning for signal/image processing, and smart ultrasound tissue characterization. He is a Senior Member of IEEE Engineering in Medicine and Biology Society (EMBS) and IEEE Ultrasonics, Ferroelectrics, and Frequency Control (UFFC). He has many publications to his credit and served as editor for books in the areas of his research interest.