Computer Vision and Robotics
Description
This book consists of a collection of the high-quality research articles in the field of computer vision and robotics which are presented at the International Conference on Computer Vision and Robotics (CVR 2024), organized by Symbiosis Skills and Professional University, Pune, Maharashtra, India, during 25-26 May 2024. The book discusses applications of computer vision and robotics in the fields like medical science, defence, and smart city planning. The book presents recent works from researchers, academicians, industry, and policy makers.
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Persons
Prof. Praveen Kumar Shukla is presently working as a Professor and Head in the department of Computer Science & Engineering, Babu Banarasi Das University, Lucknow. He is Ph. D. in Computer Science & Engineering from Dr. A P J Abdul Kalam Technical University, Lucknow. He is B. Tech in Information Technology and M. Tech. in Computer Science & Engineering. His research area includes Fuzzy Systems (Interval Type-2 Fuzzy Systems and Type-2 Fuzzy Systems), Evolutionary Algorithms (Genetic Algorithms), Genetic Fuzzy Systems, Multi-Objective Optimization using Evolutionary Algorithms, Big Data Analytics and Internet of Things. He has published many Papers in National Conferences, International Conferences and International Journals. He has also published a book "Introduction to Information Security and Cyber Laws" in 2014 with Dreamtech Publishers and published a patent on "Social Media based Framework for Community Moblisation during and post Pandemic" in 2021.He completed one Research Project on "Particle Swarm Optimization Based Electric Load Forecasting" sponsored by Dr. APJ Abdul Kalam Technical University under TEQIP-III scheme. He is the member of IEEE (Computational Intelligence Society), USA, International Association of Computer Science and Information Technology (IACSIT), Singapore, International Association of Engineers (IAENG), Hong Kong, Society of Digital Information and Wireless Communications (SDIWC), Institutions of Engineers, India and Soft Computing Research Society (SCRS), India.
Dr. Abhishek Bhatt is presently working as Professor and Director in the School of Data Science at the Symbiosis Skill and Professional University, Pune. He received his engineering degree in Electronics and Communication and M.Tech. in Digital Communication in 2003 and 2008, respectively. He receives his Ph.D. degree in Machine learning and Computer Vision domain from the Indian Institute of Technology Roorkee in 2016. There are three different patents to his name in the domain of Artificial Intelligence and data science. He has worked with various industries like Samsung Research Institute Bangalore, TCS Research, etc. on different industrial problems. He is also working with Solytics Partners, Pune on various projects related to Financial Data Analysis, and Time-series Analysis. With an experience of more than 15 years in teaching, he is the author of more than 80 journal/conference research papers and also reviews the papers submitted to some top-notch journals like IEEE Access, and IEEE Transactions, etc. in the domain of Data Science, Machine Learning, Deep Learning, and Stochastic Modelling. His current research interests include Data Analysis, Data Visualization, Computer Vision, Machine Learning, Pattern Recognition, IoT, and Cloud Computing. He is an active member of various societies like IEEE, IET, and IETE. He is also an academic council member of the CTMS Society. He is associated with the Board of studies of various engineering institutes in Maharashtra and abroad. He has chaired various international conferences in India and abroad. Presently at the Symbiosis Skill and Professional University (SSPU), he is a core committee member for various portfolios at the school as well as University level.
Dr. Himanshu Mittal is an associate professor in the Department of Artificial Intelligence and Data Sciences, Indira Gandhi Delhi Technical University for Women, India. He received his Ph.D. in the field of computer vision under the supervision of Dr. Mukesh Saraswat. The keen research areas of Dr. Mittal are image analysis, machine learning and evolutionary algorithms. He has an excellent academic record as well as a research background with papers in reputed journals including IEEE Transactions. Also, he has been the co-principal investigator of the research project funded by the Science and Engineering Research Board, Department of Science and Technology, India. Dr. Mittal is also a reviewer of many international journals and conferences.
Prof. Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artificial Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.
Content
1. Securing IoT Enabled Financial Transactions with Artificial Intelligence.- 2. Fruits Quality Detection using Hybrid CNN-SVM Model.- 3. Advancing Alzheimer's Diagnosis Integrating Transfer Learning with Support Vector Machine for Enhanced Disease Classification.- 4. Machine Learning Based Landslide Prediction in Karnataka's Ghats Region.- 5. A Review of An efficient authentication mechanism for Wireless Sensors Networking Focused on the IIoT and its comparative analysis.- 6. Comparative Evaluation of Transfer Learning Models for Accurate Plant Disease Detection.- 7. Circuit Defect Inspect Circuit board defect detection using Modified Faster R-CNN.- 8. Data-Driven Insights into Polar Sea Ice Dynamics A 2017-2022 Analysis Using AMSR2 Satellite Data.- 9. Video Processing-Based Real Time Automobile Parts Defect Detection and Classification Using Deep Neural Network A Comprehensive Survey.- 10. Optical Satellite Imaging for Glacial Velocity Analysis Insights from Sikkim Glaciers Using Computer Vision Techniques.