Artificial Intelligence: Theory and Applications
Description
This book features a collection of high-quality research papers presented at International Conference on Artificial Intelligence: Theory and Applications (AITA 2025), held during 1-2 August 2025 in Bengaluru, India. The book is divided into three volumes and presents original research and review papers related to artificial intelligence and its applications in various domains including health care, finance, transportation, education, and many more.
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Persons
Dr. Antorweep Chakravorty is an Associate Professor at the University of Stavanger. His current research and development work is in the field of applied Blockchains, Big Data, Large Scale Machine Learning, and Data Privacy. He has an interest in real-world problems, especially development of privacy enabled data-driven services in smart energy, healthcare, and smart city domains. Antorweep completed his PhD. in 2015 with a thesis on Privacy Preserving Big Data Analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching and supervision.
Dr. Hussain is working at University of Canberra as Associate Professor of Biomedical Robotics. Prior to that he has worked as lecturer at University of Wollongong, Australia. Dr. Hussain has obtained his PhD in Mechanical Engineering from the University of Auckland, New Zealand in 2013. His research interests include assistive and rehabilitation robotics, compliant actuation of robots, robot mechanism design and optimization, non-linear dynamics and control of robotic systems, human-robot interaction, biomechanical modelling, engineering education and micro electro-mechanical systems (MEMS). Dr. Hussain has published more than 65 papers in the prestigious journals of the field.
Dr. Rajani Kumari is currently an Assistant Professor at IBS, Bangalore, Off-Campus Centre of ICFAI Foundation for Higher Education (IFHE) University, India. Previously she was an assistant professor at IIIM, Jaipur and St. Xavier's College Jaipur, CHRIST University. She received the PhD degree in computer science in 2015, the MCA and BCA from University of Rajasthan in 2010 and 2006 respectively. She has published more than forty research papers in various international journals/conferences and participated in many national and international conferences and workshops. She edited some special issue in Taylor & Francis and Inderscience journals including Journal of Information and Optimization Sciences (JIOS) and Int. J. of Intelligent Information and Database Systems (IJIIDS). Her research interests include Nature Inspired Algorithms, Swarm Intelligence, Soft Computing, and Computational Intelligence.
Content
Synthetic Human Face Generation using DCGAN and Fake Image Classification with Feature-based Explanation.- Combining Audio and Video Analytics in a Multi-Modal Method for Fight Detection in Surveillance Systems.- Blockchain-Powered Claims Validation for Enhancing Trust in Health and Auto Insurance Ecosystems.- Anomalous Human Activity Recognition in Transformer based Video Surveillance System.- Automating Generation of UML sequence diagram using LLM.- An Explainable Deep Learning Framework for Mammogram-Based Tumor Classification Using GoogleNet and Grad-CAM.- Personalised Image and Video Synthesis using Conditional Generative Adversarial Networks.- Real Time Health Monitoring System using AD8232 and MAX30100 sensor with ESP8266.- Contextual Understanding Enhancement in LLMs using Adaptive Attention Framework.- Advancement in Text-to-Sql System using Large Language Model(LLMs): A Review.-Seizure Prediction and Classification from EEG Data using Logistic Regression and Long Short Term Memory Networks.- INSIGHT: A Survey of In-Network Systems for Intelligent, High-Efficiency AI and Topology Optimization.- SliceNet: An Explainable Deep Learning Framework for CT-Based Bladder Cancer Stage Classification using Lightweight CNNs.- A Retrieval-Augmented Generation Pipeline for Summarizing Research Papers using Local LLMs.- Data-Driven Flood Forecasting: A Comprehensive Evaluation of Regression and Ensemble Models.