This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.
Focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. Topics include Parkinson’s disease diagnosis, big image data processing, N-grams for image classification, medical brain images, credit score improvisation, vision-based lane and vehicle detection, damaged vehicle parts recognition, partial imag
1. Visual Quality Improvement Using Single Image Defogging Technique
2.
A Comparative Study of Machine Learning Algorithms in Parkinsons Disease
Diagnosis: A Review
3. Machine Learning Algorithms for Hypertensive
Retinopathy Detection through Retinal Fundus Images
4. Big Image Data
Processing: Methods, Technologies, and Implementation Issues
5. N-grams for
Image Classification and Retrieval
6. A Survey on Evolutionary Algorithms for
Medical Brain Images
7. Chatbot Application with Scene Graph in Thai Language
8. Credit Score Improvisation through Automating the Extraction of Sentiment
from Reviews
9. Vision-Based Lane and Vehicle Detection: A First Step Toward
Autonomous Unmanned Vehicle
10. Damaged Vehicle Parts Recognition Using
Capsule Neural Network
11. Partial Image Encryption of Medical Images Based
on Various Permutation Techniques
12. Image Synthesis with Generative
Adversarial Networks (GAN)
Chiranji Lal Chowdhary is an Associate Professor in the School of Information Technology & Engineering at VIT University, where he has been since 2010. He received a BE (CSE) from MBM Engineering College at Jodhpur in 2001, and MTech (CSE) from the M. S. Ramaiah Institute of Technology at Bangalore in 2008. He received his PhD in Information Technology and Engineering from the VIT University Vellore in 2017. From 2006 to 2010 he worked at M. S. Ramaiah Institute of Technology in Bangalore, eventually as a Lecturer. His research interests span both computer vision and image processing. Much of his work has been on images, mainly through the application of image processing, computer vision, pattern recognition, machine learning, biometric systems, deep learning, soft computing, and computational intelligence. As of 2020, Google Scholar reports over 270 citations to his work. He has given a few invited talks on medical image processing. Professor Chowdhary is editor/co-editor of three books and is the author of over 40 articles on computer science. He filed two patents deriving from his research.
Dr. Thippa Reddy Gadekallu is currently working as Associate Professor in the School of Information Technology and Engineering, VIT, Vellore, Tamil Nadu, India. He obtained his BTech in CSE from Nagarjuna University, India; MTech in CSE from Anna University, Chennai, Tamil Nadu, India; and completed his PhD in VIT, Vellore, Tamil Nadu, India. He has more than 14 years of experience in teaching. He has published more than 50 international/national publications. Currently, his areas of research include Machine Learning, Internet of Things, Deep Neural Networks, Blockchain, Computer Vision. He filed one patents deriving from his research.
Dr. B. D. Parameshachari is currently working as a Professor and Head in the Department of Telecommunication Engineering at GSSS Institute of Engineering & Technology for Women, Mysuru, affiliated to Visvesvaraya Technological University (VTU), Belagavi, Karnataka, India. Under his leadership, the Dept. of TCE, GSSSIETW has Achieved NBA (Tier-II) Accreditation Twice. He completed his BE degree in Electronics and Communication Engineering from Kalpatharu Institute of Technology, Tiptur and MTech degree in Digital Communication Engineering from BMS College of Engineering, Bangalore. and completed his PhD in ECE from Jain University, Bangalore. He has a total 17+ years of teaching and research experience, and he has worked in various positions and at places like Karnataka, Kerala, and Mauritius (abroad). He is recognized as a Research Guide at VTU, Belagavi, and currently, five research scholars were pursuing PhD degrees under his supervision. Under his leadership, his affiliated department was successfully approved by various accreditation bodies and received certification. He was instrumental in establishing collaboration between GSSSIETW and Multimedia University, Malaysia and also with University of Sannio, Italy.
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