Proceedings of International Conference on Artificial Intelligence and Networks : ICAIN 2025, Volume 3.DE (Lecture Notes in Networks and Systems)

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Proceedings of International Conference on Artificial Intelligence and Networks : ICAIN 2025, Volume 3.DE (Lecture Notes in Networks and Systems)

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Description

This book presents selected papers from International Conference on Artificial Intelligence and Networks (ICAIN 2025), organized by BITS Pilani, Dubai Campus, in association with the Indian Institute of Information Technology, Allahabad, and Universal Inovator on 6 7 October 2025. The topics covered in the book are deep learning, machine learning, natural language processing, data science and analytics, cybersecurity and privacy, cloud computing, and wireless and mobile networks.

FundusInsight: A Fine-Tuned ResNet50 Framework for Automated Grading of Diabetic Retinopathy.- Optimizing Soleus Muscle Stimulation for Glucose and Lipid Regulation: A Mathematical Modeling and Particle Swarm Optimization Approach.- Cloud-Driven Transformation of Enterprise HCM Systems: A Strategic Framework for Mitigating from PeopleSoft to Oracle Cloud HCM.- Advanced Vision Perception Systems for Autonomous Driving: FRCNN, MOS-Net, and CNN Integration.- Advanced Design Modelling & Implementation Of Digital Twin For Acopostrak Using Automation Studio: Techniques And Results.- Personalized Drug Risk Prediction Using Digital Twin and Machine Learning Framework.- Comprehensive Review of Security Techniques for VANETs: Blockchain, Machine Learning, and Optimization Approaches.- Gestational Diabetes Predictions using AI model GAN.- Towards Accurate and Efficient Diagnosis of Celiac Disease Based Deep Learning Approach Using Biopsy Image Analysis.- ISLNet: A Landmark -Driven Framework for Accurate and Scalable Indian Sign Language Recognition.- Federated Learning-Based Intrusion Detection for Resource-Constrained IoT Devices Using Lightweight Neural Networks.- AwakenGuard: AI Powered Driver Vigilance System.- Transforming Pharmaceutical Care: A Digital Approach to Enhancing Patient Engagement.- Smart Industrial Performance Assessment and Monitoring Using Cloud Based Solutions.- Mathematical Modeling and Interpretable Deep Learning for Automated IHC.- Exploring Deep Metric Learning for Pneumonia Detection in the Limited Data.- NextGenViDx: A Federated and Explainable Vision-Transformer Framework Enhanced with Generative AI for Real-Time, Accurate, and Ethical Viral Disease Detection Across Diverse Clinical Modalities.- Spotting the Fakes: LSTM-Powered Detection of Deceptive Online Reviews.- Secure-HashChain IoMT: A Blockchain and Secret-sharing Framework for Privacy-Preserving Remote Patient Monitoring.- Evaluating Few-Shot Learning Capabilities of Large Language Models as a Step Toward Artificial General Intelligence.- Enhanced Federated Learning for Network Intrusion Detection: A Comprehensive Privacy-Preserving Approach.- ESADN: An Enhanced Spatial Attention Network for Road Accident Detection.- Investigating New Approaches for Sentence Jnderstanding Using Advanced Computational Models.- Early Threat Engagement Via Honeypot-Derived Learning In Cyber Defense Systems.- Hybrid Deep Learning and Generative Augmentation Framework for Robust Multi-Metric Lung Cancer Detection: A Comparative Evaluation of CNN, RNN, and Lightweight Architectures.- A Variable-Size Block Cipher Utilizing a Novel Six- Dimensional Chaotic System and an Auto-Key Encryption Mechanism.- Hawkeye- An Interactive Intelligent Platform for Cybersecurity Awareness through Gamification.- Enhanced AI-Driven Project Management Framework for Complex Space Exploration Missions: A Case Study Analysis of the James Webb Space Telescope.- A Hybrid CNN-SVM Edge-Enabled NIDS Framework for IoT Security.- Vision Transformer-Based Model for Early Detection of Skin Cancer from Dermoscopic Images.- Cyber Threat Dynamics: Strategic Mitigation for Digital Security.- DetBias: A Framework for Detecting Bias in NLP Classifier Models.- Bird Detection using CNN on Audio Classification Datasets.- Toward Next-Generation Sensing: Optical Fiber Sensor-Based Network Technologies (OFSNT).- Earthquake prediction using machine learning models (MARS, KNN, KR, RVM).

Prof. Bal Virdee graduated with a BSc (Engineering) Honours in Communication Engineering and MPhil from Leeds University, UK. He obtained his PhD from the University of North London, UK. He worked as an academic at Open University and Leeds University. Prior to this, he was a research and development Electronic Engineer in the Future Products Dept. at Teledyne Defence (formerly Filtronic Components Ltd., Shipley, West Yorkshire), and at PYE TVT (Philips) in Cambridge. He has held numerous duties and responsibilities at the university, i.e., Health and Safety Officer, Postgraduate Tutor, Examination s Officer, Admission s Tutor, Short Course Organiser, Course Leader for MSc/MEng Satellite Communications, BSc Communications Systems and BSc Electronics.

Prof. Sérgio D. Correia received his Diploma in Electrical and Computer Engineering from the University of Coimbra, Portugal, in 2000, the master s degree in Industrial Control and Maintenance Systems from Beira Interior University, Covilhã, Portugal, in 2010, and the Ph.D. in Electrical and Computer Engineering from the University of Coimbra, Portugal, in 2020. Currently, he is an Associate Professor at the Portalegre Polytechnic University, Portugal. He is also a Researcher at COPELABS - Cognitive and People-centric Computing Research Center, Lusofona University of Humanities and Technologies, Lisbon, Portugal, and VALORIZA - Research Center for Endogenous Resource Valorization, Portalegre Polytechnic University, Portalegre, Portugal, and has worked with several private companies for more than 20 years.

Prof. (Dr.) Abhishek Swaroop completed his B.Tech. (CSE) from GBP University of Agriculture & Technology, MTech. from Punjabi University Patiala, and Ph.D. from NIT Kurukshetra. He has Industrial experience of 8 years in organizations like Usha Rectifier Corporations and Envirotech Instruments Pvt. Limited. He has 22 years of teaching experience. He is actively engaged in research. He has more than 60 quality publications out of which 8 are SCI and 16 Scopus. Two of his Ph.D. Scholars have completed his Ph.D. from NIT Kurukshetra and IIT Dhanbad. He is currently supervising a Ph.D. student from AKTU Lucknow.

Dr. Narina Thakur completed her Ph.D. in Computer Science and Engineering from Amity University Uttar Pradesh, India, in 2019, with a focus on Information Retrieval and Machine Learning. She earned a Gold Medal for her Bachelor of Technology (B.Tech) in Computer Science & Engineering from Himachal Pradesh University and holds a Master of Technology (M.Tech) in Information Technology from Punjab Technical University, India. Currently, Dr. Thakur serves as the Head of the Research and Innovation Committee and is an Assistant Professor in the Department of Computing at the University of Stirling, RAK Campus, UAE. With 23 years of teaching experience and an H-index -14, Dr. Thakur has published 5 SCI-SCIE indexed and more than 75 research papers in peer reviewed Scopus Indexed International Journals, ACM SIGARCH, Elsevier, IEEE, and International Conferences. She has authored several books on Algorithms, Programming, and Operating Systems. Her research areas include Computational Intelligence, Artificial Intelligence, Computer Vision, and IoT.

Dr. Sujala D. Shetty is an Associate Professor and Head in the department of Computer Science. She is working with BITS Pilani, Dubai Campus since September 2002. She has wide academic and research experience. She has handled significant administrative responsibilities. She has handled classes for both undergraduate, postgraduate and distance education students. Her research areas are Big Data, Artificial Intelligence, IoT, Web Services, NLP. She completed her bachelor s from Bangalore Institute of Technology in 1994, her master s from Manipal Institute of Technology in 2004 and her PhD from BITS Pilani, Pilani Campus in 2010, respectively.


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