This book presents a selection of high-quality research papers accepted for presentation at the Fifth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2025). The conference was jointly organized by the Department of IoT & Intelligent Systems, Manipal University Jaipur, India, in collaboration with CNR-Nanotec at the University of Calabria, Italy, and Hansraj College, University of Delhi, India, and was held from June 04 to 06, 2025. ICICV 2025 was conducted in hybrid mode, with in-person sessions hosted at CNR-Nanotec, University of Calabria, Italy, and virtual sessions facilitated by Manipal University, Jaipur, and Hansraj College, University of Delhi.
Enhancement of Medical Microscopic Images Using Segmentation and an
Optical Attenuation Model as a Basis for Adaptive Histogram Equalization.-
Crowd Counting: A VGG-Driven Convolutional Framework.- Benchmarking and
Results of Auto-PCOS Classification Challenge.- Enhancing Human Action
Recognition Using Convolutional Neural Networks with Squeeze, Excitation
Blocks, and Optical Flow.- Dual-Path Encoder-Decoder (DPED) with Feature
Fu-sion and Dual-Stage Decoding for Precise Tumor Seg-mentation in Breast
Histopathology Images.- Understanding Customer Experience: Sentiment Analysis
of Bengali Text-based Hotel Reviews Using Machine Learning Approach.- AI for
Agriculture: Detecting Black Gram Diseases with Deep Learning and Explainable
AI.- Brain Tumor Detection via MRI: A Dual AI Approach for Accurate
Classification.- An Approach using EfficientNetB4 for Gender Determination.-
PyEDA: A Python-Based Tool for Protein Dynamics Analysis Using Essential
Dynamics Approach.- AI-Driven Breast Cancer Classification and Personalized
Stage-Specific Treatment Recommendations.- Stress Monitoring in Healthcare:
An Ensemble Machine Learning Framework Using Wearable Sensor Data.-
Harnessing AI Agents to Advance Research on Refugee Child Mental Health.-
Practical Portfolio Optimization with Metaheuristics: Pre-assignment
Constraint and Margin Trading.- Deep Learning Based Weed Identification in
Crops using Improved CNN-PFO.- Enhancing Squamous Cell Carcinoma Detection in
Pap Smears Using Multiscale Feature Refinement with Dilated Spatial Pyramid
Pooling.- Medical Images Fusion using Signal Decomposition Methods and
Implementation on an Embedded Platform.- CA-ANN based Predictive Modeling of
Land use Land cover, Urban Fragmentation and Seasonal Land Surface
Tempera-ture: Insights from Semi-arid Climate City.- Distance aware
Clustering and Path Construction in Mobile Sink-based Wireless Sensor
Networks.- DeepTrafficFlow: A Deep Learning Approach for Real-Time Traffic
Monitoring and Congestion Reduction in Smart Cities.- Progression of
Idiopathic Pulmonary Fibrosis (IPF) using Deep Learning.- Predicting
Pedestrian Intentions for Intelligent Transport Systems.- Deep Learning-Based
Malayalam Sign Language Recognition Using 3D CNNs.- BlockEnhance: A
Blockchain Based Secure & High-Quality Image Transfer.- Drought Analysis in
Vidharbha Using ARIMA and LSTM.- Advancing Artificial Immune System-Based
Anomaly Detection.- Integrating Language and Vision Models for Real-Time
Assistance for the Visually Impaired.- ChampionView: A Recommendation
Engine.- Web-Based Customer Review Analysis and Fake Review Detection Using
NLP.- Comparative Analysis of Machine Learning Models for Electric Vehicle
Charging Patterns.- Retrieval-Augmented Generation Approach for MediaSearch.-
Advancing Soil Moisture Estimation Using Sentinel-1 and Deep Learning
Techniques.- Investigation of Tidal Impacts on Mangrove Health and IoT-Driven
System for Conservation.- Evolutionary Algorithm-Based Model Merging
Framework for Small Multimodal Models.- SPY-BOT, a Robot that works on LIDAR
SLAM.- Enhancing Data Security in Healthcare 4.0 Using Selective Encryption.-
Car Price Prediction and Recommendation System using Machine Learning.-
Real-Time Pothole Detection using YOLO and GIS Mapping.- Deep Neural Networks
for Earth Observation: Satellite Classification with Modern Architectures.-
Enhanced Liver Tumor Segmentation and Interpretation using Hybrid U-Net and
Explainable AI for Clinical Diagnostics.- Alzheimer Diagnosis and Cost
Estimation Bot.- Multi-Modal Boundary-Aware Attention U-Net for Brain Tumor
Segmentation.- AI-Based Traffic Flow Optimization using Quantum- Inspired
Techniques.- SEViT-GAN: Attention based GAN with SE Residual blocks for Image
Inpainting.- Prevention of Examination Paper Leakage using Threshold
Decryption.- Blind Data Hiding Approach Based on Digit Substitution for 3D
Mesh Object.- Enhancing Smart Home Security Through Dynamic Authentication
for Voice-Activated Commands.- High-Accuracy Speech Emotion Recognition Using
MFCC and LSTM with Optimized Deep Learning Architecture.- Drone-based Parking
Occupancy Monitoring and Recommendation.
Deepak Sinwar is an associate professor in the Department of IoT and Intelligent Systems, Manipal University, Jaipur, Rajasthan, India. He holds a Ph.D. and M.Tech. in Computer Science and Engineering (2016 and 2010, respectively) and a B.Tech. (with honors) in Information Technology (2008). He is an enthusiastic and motivating academician with more than 15 years of research and academic experience. His research interests span Computer Vision, Meta-heuristics, Ad-hoc Networks, Data Mining, and Reliability Engineering. He has authored more than 50 publications in reputed peer-reviewed journals, conference proceedings, and book chapters. He actively contributes to academic publishing through editorial roles, including book editing and guest editing special issues with leading publishers. Throughout his career, he has organized and participated in numerous international conferences and workshops. Vijaypal Singh Dhaka is a dynamic and visionary professor of Computer Science with over two decades of academic and industry experience. Known for his motivational leadership and student-centric approach, he has chaired several international conferences and held key positions such as the dean-academics, director of CSE School, director of Entrepreneurship Cell, and chief editor of an international journal. With 130+ publications, 30+ IPRs, and supervision of 17 Ph.D. scholars, his contributions reflect a strong commitment to research excellence. He earned his Ph.D. from Dr. B. R. Ambedkar University, Agra, in handwriting recognition using image processing. His research interests include AI, ML, Image Processing, and Pattern Recognition. He is also actively engaged in executing government-funded research projects, contributing impactful solutions to pressing technological challenges. He is presently serving at Manipal University, Jaipur, as a professor of Computer Science and Dean Quality and Accreditation. Thinagaran Perumal is the recipient of 2014 Early Career Award from IEEE Consumer Electronics Society for his pioneering contribution in the field of consumer electronics. He completed his Ph.D. at Universiti Putra Malaysia, in the area of smart technology and robotics. He is currently a senior lecturer at the Department of Computer Science, a faculty of Computer Science and Information Technology, Universiti Putra Malaysia. His research interests are toward interoperability aspects of smart homes and Internet of Things (IoT), wearable computing, and cyber-physical systems. Thina is also heading the National Committee on Standardization for IoT (IEC/ISO TC / G/16) as the chairman since 2018. He is an active member of IEEE Consumer Electronics Society and its Future Directions Committee on Internet of Things. Eugenio Vocaturo is a researcher at the Institute of Nanotechnology, National Research Council of Italy (CNRNanotec), Rende, Italy, where he leads the Artificial Intelligence Laboratory. He holds Laurea in Management Engineering (2002), Master in Industrial Engineering Management (2006), Master in Finance (2016), and Ph.D. in Information and Communication Technologies (2020). He has decades of experience as the company director, production and logistics manager of business groups, head of editorial production of important IT publishing. His research focuses on AI, Machine Learning, Deep Learning, Explainable AI, and Computer Vision. Since 2024, he has been member of the Evaluation Expert Group (GEV) for sector ING-INF/05 within the framework of the Italian Research Quality Evaluation (VQR 20202024), promoted by ANVUR.
