
Computational Intelligence in Data Science
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The three-volume set IFIP ICCIDS 748, 749 and 750 constitutes the refereed post-conference proceedings of the 8th IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2025, held in Chennai, India, during February 12-14, 2025.
The 91 papers including 70 regular papers and 21 short papers included in these proceedings were carefully reviewed and selected from 317 submissions. The papers are organized in the following topical sections:
Part I: Computer Vision for Real World Applications.
Part II: Computer Vision for Real World Applications; Emerging Trends in AI for Speech and Text.
Part III: Emerging Trends in AI for Speech and Text; Computational Intelligence for Secure, Smart and Sustainable Applications
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Content
. - Computer Vision for Real World Applications.
.- AgriGuardNet: A Unified Approach to Plant Disease and Pest Detection.
.- Advanced Plant Disease and Pest Detection for Sustainable Agriculture.
.- Design of a unified framework for Automatic Detection of FOD (Foreign Object Debris) in Airport Runways.
.- A Low-Cost Vision-Based Framework for Autonomous Driving Using YOLO, MiDaS, and Stereo Vision.
.- A Secure System to Detect Animal Intrusion and Notify Users in a Farmland.
.- The Synergy of Federated Learning and IoT: Pioneering Privacy and Efficiency in Decentralised Systems.
.- Multi-Class Diagnosis of Ocular Diseases in Fundus Images using Fine-Tuned EfficientNetV2B3 Model with Self-Attention.
.- SMARTSPICEVISION: Revolutionizing Spice Authentication for Enhanced Detection, Grading, and Quality Control.
.- Deep Learning-Based Comparative Analysis for Endometriosis Classification.
.- Kidney Stone Detection in CT Scans: A Hybrid Approach with Machine Learning and Deep Learning.
.- Efficient Yoga Pose Classification Using Deep Neural Networks.
.- AI-Driven Multi-modal Story Generator by Integrating Image Understanding with Creative Narrative Generation Using Gemini and OpenAI APIs.
.- CureFinder - A Smart Health Care Aide for Predictive Analysis of Disease.
.- Eyesight: Integrative AI For Non-Invasive Diabetic Retinopathy Detection Using Pupillometry and Ensemble Deep Learning.
.- Topple-Net: A Modified U-Net Architecture for Classification of Diseased Tomato and Apple Leaves in Uncontrolled Environments.
.- Revolutionizing Seed Plant Classification: CNN Approaches For Enhanced Accuracy.
.- Emerging Trends in AI for Speech and Text.
.- Multiactivity Agent Using LLM For YouTubers.
.- Speech to Text Recognition by Machine Learning.
.- Hope Speech Detection and Classification Using Machine Learning and Deep Learning Techniques.
.- AI to conquer Stage fright.
.- Voice Unlocked: Transforming Speech Therapy for Special Children with VR and Gesture Animation.
.- Deep Learning Enhanced Suicidal Detection in Social Media.
.- Predicting Diseases from Symptoms Using Machine Learning Models and Open AI.
.- Transforming Lives: AIoT-Driven Deep Learning for Real- Time Speech Assistance for the Ophthalmologically Impaired.
.- Integrating A-LSTM with XGBoost for Improved Crop Price Prediction.
.- Experimenting AI-Driven Haiku Generation through Reinforcement Learning and User Feedback.
.- Comparative Insights into Modern Architectures for Paraphrase Detection.
.- Speech Emotion Detection for Tamil Language: Performance Evaluation of Deep Learning Models.
.- Enhancing Cardiac Pathosis Evaluation Bot: An AI-Powered Multimodal Approach for Risk Assessment.
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