Deep Learning and Visual Artificial Intelligence
Description
This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI 2025), held at Jodhpur Institute of Engineering and Technology, Jodhpur, India, during December 20-21, 2025. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition.
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Persons
Dr. Vishal Goar is an Assistant Professor in the Department of Computer Applications at Engineering College Bikaner, Rajasthan, India. He has over 15 years of experience in teaching, research, and academic administration. He served as Dean (Research) at Bikaner Technical University, Bikaner from March 2022 to December 2023, contributing significantly to the university's research initiatives and academic development. Dr. Goar's research interests include Artificial Intelligence, Cloud Computing, Data Mining, and Software Engineering. He has authored and edited more than 15 books with reputed publishers such as Springer, ACM, and Scholars-Press, and published over 50 research papers in indexed journals and international conferences. He has also guided multiple Ph.D. scholars and holds several Indian and international patents.
Dr. Jyoti Gajrani is the Head of the Department of Computer Science & Engineering (CSE, IT, and Cyber) at Government Engineering College, Ajmer. She holds an M.Tech. from IIT Bombay and a Ph.D. from MNIT Jaipur, with over 20 years of teaching and research experience. Her primary research areas include cybersecurity, privacy, and mobile malware analysis. She was honored with the AICTE VISVESVARAYA Best Teacher Award 2021 at the national level. Dr. Gajrani has contributed to the development of key government digital initiatives like the Ajmer Police Traffic App and the E-Lecture App, and has led two major funded research projects worth ?35 lakhs. She has published around 45 research papers, authored one book and seven book chapters, and delivered expert talks at premier institutions including IITs and NITs.
Jungpil Shin (Senior Member, IEEE) received the B.Sc. degree in computer science and statistics and the M.Sc. degree in computer science from Pusan National University, South Korea, in 1990 and 1994, respectively, and the Ph.D. degree in computer science and communication engineering from Kyushu University, Japan, in 1999, under a scholarship from the Japanese Government (MEXT). He was an Associate Professor, a Senior Associate Professor, and a Full Professor with the School of Computer Science and Engineering, The University of Aizu, Japan, in 1999, 2004, and 2019, respectively. He has co-authored more than 450 published papers for widely cited journals and conferences. His research interests include pattern recognition, image processing, computer vision, machine learning, human-computer interaction, non-touch interfaces, human gesture recognition, automatic control, Parkinson's disease diagnosis, ADHD diagnosis, user authentication, machine intelligence, bioinformatics, and handwriting analysis, recognition, and synthesis.
Adam Slowik (Senior Member, IEEE) received the B.Sc. and M.Sc. degrees in computer engineering and electronics, in 2001, and the Ph.D. degree in electronics with distinction from the Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland, in 2007, respectively, and the Dr. Habil degree in computer science (intelligent systems) from the Department of Mechanical Engineering and Computer Science, Czestochowa University of Technology, Czestochowa, Poland, in 2013.
Content
Code Smell Detection via Pearson Correlation and ML Hyperparameter Optimization.- Influence of AI-Based Talent Analytics on Employee Productivity and Retention: The Roles of Job Satisfaction and Leadership Support.- Sustainable Modernization of Medium-Voltage Power Grids Using a Multi-Criteria Decision-Support Framework.- Performance Comparison of Clustering K-SVD with MOD, K-SVD, SimCO, and BLOTLESS-Update in Sparse Dictionary Learning.- An Enhanced learning model for Detection of digits in images using deep learning techniques.- Enhancing the Interpretability of CNN-Based Brain Tumor Detection in MRI Scans Using Explainable AI Techniques.- Privacy-Aware Consortium BlockchainArchitecture for Protecting IoMTHealthcare Data.