About the Book
This book presents high-quality research papers presented at International Conference on Computational Intelligence (ICCI 2024) held at Sardar Vallabhbhai National Institute of Technology, Surat, India, during 24-26 December 2024. The topics covered are artificial intelligence, neural network, deep learning techniques, fuzzy theory and systems, rough sets, self-organizing maps, machine learning, chaotic systems, multi-agent systems, computational optimization ensemble classifiers, reinforcement learning, decision trees, support vector machines, hybrid learning, statistical learning, metaheuristics algorithms, machine vision, Internet of Things, image processing, image segmentation, data clustering, sentiment analysis, big data, computer networks, signal processing, supply chain management, web and text mining, distributed systems, bioinformatics, embedded systems, expert system, forecasting, pattern recognition, planning and scheduling, time series analysis, human-computer interaction, web mining, natural language processing, multimedia systems, and quantum computing.
Table of Contents:
Photovoltaic Substation Voltage Forecasting Optimization Using Modified Metaheuristic and Gated Recurrent Unit Networks.- Enhancing Neural Architecture Search: A Comparative Optimization Framework.- Deep Learning-Driven Blood Vessel Segmentation for Early Detection and Classification of Diabetic Retinopathy.- A Comprehensive Hybrid Metaheuristic Algorithm: Leveraging Coyote and Chimp Optimization for Optimal Performance.- Modifying Metaheuristic Optimizers for Hyperparameter Tuning of Machine Learning Models Tackling Malicious Node Detection in Blockchain Networks.- Innovative Skin Disease Diagnosis: A Hybrid Learning Framework for Skin Cancer Detection.- Depth Estimation for Autonomous Vehicles with Enhanced Perception.- Hybridizing CNN with an LSTM Back-End for Univariate Rainfall Forecasting.- Enhancing ECG Abnormality Detection using Image Processing and Transfer Learning Approach.- Enhancing Transformer Efficiency through Active Learning and Knowledge Distillation.- Enhancing Dyslexia Classification using Feature Selection and Ensemble Learning Models on Eye-Tracking Data.- Classification of Arrhythmia Data and QRS Peak Detection for Feature Extraction using SVM Classifiers.- Effects of Environmental and Agronomic Factors on Crop Yield at Different Phenological Stages.- Classification Models for Predicting Accident Severity and the Impact of Factors Contributing to Severity.- A Weighted Deep Learning Approach to Identify Nucleic Acid-Binding Proteins.- Predictive Analytics in Financial Transactions: A Comparative Study for Customer Risk Assessment and Revenue Prediction.- Enhancing Renewable Energy Planning: Machine Learning-based Solar Radiation Prediction.- From Text to Treatment: Predicting Mental Health Needs through Language Analysis and Machine Learning.- A Systematic Review of Deep Learning Techniques for Enhancing Public Safety through Video Surveillance.- Particle Swarm Optimization Algorithm for Quasi-total Roman Domination.- Automatic Detection of Erythrocytes for Sickle Cell Disease Identification Based on YOLOv8n Network.- Exploring the Effectiveness of Collaborative and Content-Based Filtering Techniques in Movie Recommendation Systems with Explainable AI.- Deep Learning-Based Classification of Lung, Kidney, and Breast Cancer Tumor Tissues using Whole Slide Images from the TCGA Database.- Foot Pressure and 3D Skeleton based Multimodal Approach for Pathological Gait Classification.- A Study on Generative Adversarial Network (GAN), Neural Style Transfer (NST) and Autoencoders.- MTL-SDCNN-Based Pre-and Post-Harvest Disease Prediction of Wheat and Paddy Crops.- Mining Association Rules among Biophysical Water Parameters using Improved Frequency Pattern Growth Algorithm.- Deep Learning Approach for Detection and Classification of Alzheimer’S Disease.- Advancements in Voice Pathology Detection: A Comprehensive Bibliometric and Visual Network Analysis.- Railway Track Crack Detection System.- Enhancing Security with a Custom Authenticator App and Comprehensive Zero Trust Architecture.- Super-Resolution of MRI Images using Deep Learning for Enhanced Medical Diagnostics using Altair Rapidminer Studio.- Exloring the Role of ICT Tools for Autism Spectrum Disorder Support: A Survey-Based Study.- Advanced Data Analytics for Organ Donation Tracking using AI and Blockchain.- Adaptive Trust Based Secure Routing Protocol for Wireless Adhoc Network.- Stochastic Particle Swarm Optimization with Bayesian Inference for Hyperparameter Optimization in CNN for Image Classification.- MultiBand Microstrip Patch Antenna for C-Band Applications.- Thoracic Disease Detection and Classification Using Chest X-rays: A Deep Learning Approach with ResNet-50 and DenseNet-121.
About the Author :
Prof. Mukesh Saraswat is a professor and associate dean (Innovation) at Jaypee Institute of Information Technology (JIIT), Noida, India. Prof. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 20 years of teaching and research experience. He has guided 04 Ph.D. students and presently guiding 04 Ph.D. students. He has published more than 80 journal and conference papers in image processing, pattern recognition, and soft computing. He was part of a successfully completed project funded by SERB, New Delhi on image analysis and one project funded by CRS, RTU, Kota. He has been an active member of many organizing committees for various conferences and workshops. Prof. Ritu Tiwari is currently working as a professor in the Department of Computer Science and Engineering at S V National Institute of Technology (SVNIT), Surat (NIT, Surat). Before joining SVNIT, Surat, she has worked as a professor at IIIT Pune, she was an associate professor in the Department of Information and Communication Technology at ABV--Indian Institute of Information Technology and Management (IIITM) Gwalior. She has 12 years of teaching and research experience. Her field of research includes Robotics, Artificial Intelligence, Soft Computing, and Applications. She has published 05 books and more than 80 research papers in various national and international journals/conferences and is the reviewer for many international journals/conferences. Dr. Mario F. Pavone is currently working as an associate professor in Computer Science at the Department of Mathematics and Computer Science, University of Catania, Italy. Prof. Pavone is focused on the design and development of Metaheuristics applied in several research areas, such as in Combinatorial Optimization; Computational Biology; Network Sciences and Social Networks. Prof. Pavone was a visiting professor with a fellowship at the Faculty of Sciences, University of Angers, France in 2016. From August 2017, Prof. Pavone is a member of the IEEE Task Force on the Ethical and Social Implications of Computational Intelligence, for the IEEE Computational Intelligence Society (IEEE CIS). Prof. Mukesh A. Zaveri is a professor at SVNIT, Surat specializing in Computer Vision, Image Processing, Audio-Speech Signal Processing, Machine Learning, Wireless Sensor Networks, and the Internet of Things at SVNIT, Surat, India. It outlines his extensive academic qualifications, including a Ph.D. from IIT Bombay, and his notable professional experience in various roles at SVNIT. Additionally, the document details his research work focused on advanced algorithms for target detection and tracking in infrared video sequences, involving complex data association methods and simulations to evaluate algorithm performance. His research interests include C on computer vision.
