Advances in Smart Computing and Applications
Description
This book constitutes the refereed proceedings of the 1st International Conference on Advances in Smart Computing and Applications, ICASCA 2025, held in Ahmedabad, India, during February 15-16, 2025.
The 25 full papers were presented in this volume were carefully reviewed and selected from 112 submissions. They focus on Machine Learning, Deep Learning, Transfer Learning, Neural Computing, Artificial Intelligence, Reinforcement Learning, Recommendation systems, Soft computing, Intelligent Systems, Pattern Recognition, Natural Language Processing, Big Data Analytics, Networks, Text Mining, Web Mining, Data Streams, Image Processing, Distributed Databases, Block Chain.
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Content
- AI Enabled Human Action Recognition.
.- Enhanced Date Fruit Classification with a Novel One-Dimensional Convolutional Neural Network.
.- Accuracy Improvement of Fish Counting in Sonar Images using Deep Learning with Double Transfer Learning.
.- Predicting Agricultural Crop Yield in Indian States Using Machine Learning Models.
.- Comparative Analysis of Machine Learning Models on Binary Classification Using Tabular Datasets: A Study on Credit Risk, Australian, and German Datasets.
.- Hybrid Multi-Objective Optimization for Efficient Workflow Scheduling in Cloud Computing Environments: A PSO-GD Integrated Approach.
.- Exploring Novel Perspective on Collaborative AI: Techniques, Challenges, and Limitation.
.- Enhanced Malicious URL Detection through Feature Significance Analysis.
.- A Smart Intelligence Intrusion Detection System Using Optimal Elephant Hardening Feature Selection with Deep Generative Adversarial Neural Network Classifier.
.- Breast Cancer Diagnostics with Deep Learning Schemes Using Multi-Image Modalities.
.- Ethical Implications of Using AI to Monitor and Regulate Dark Web Activities.
.- Analyzing AI Generated Text using various Machine Learning, Deep Learning and LLM Models.
.- Predictive Modeling and Strategic Planning for Urban Flood Risk Mitigation.
.- A Review on Deep Learning Techniques for Cervical Cancer Detection.
.- Enhanced COVID-19 Detection Using CNN and Texture-Based Feature Extraction With Gradient Boosting Ensemble learner.
.- AI for Intelligent Data Retrieval.
.- Automated Skin Lesion Detection Using Deep Learning Approach.
.- A Review on Student Behavior Detection.
.- Vcare: A Survey on Menstrual Health Awareness and Accessibility.
.- Sentiment and Comment Analysis Using Various Machine Learning Algorithms and Evaluation of Classifiers on Educational YouTube Videos.
.- Identifying fake products using Blockchain.
.- Tourism Trends Through Yelp Review Analysis.
.- Revolutionizing eLearning with Metaverse Technologies: Virtual Classrooms and Beyond.
.- Integrating Artificial Intelligence and IoT for Early Detection and Management of Fungal Diseases in Oilseed Crops.