Overview

This two-set volume CCIS 2653 and 2654 constitutes the refereed proceedings of the Second International Conference on Advances in Artificial Intelligence and Machine Learning in Big Data Processing, AAIMB 2024, held in Chennai, India, during December 12–13, 2024. The 59 full papers included in this book were carefully reviewed and selected from 434 submissions. The papers are organized in the following topical sections: Part I: artificial intelligence and data analytics; machine learning. Part II: artificial intelligence and data analytics; deep learning.

Full Product Details

Author:   Geetha Ramachandran ,  Nhu-Ngoc Dao ,  Noor Zaman Jhanjhi ,  Anuradha Muthukrishnan
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032130280

ISBN 10:   303213028
Pages:   404
Publication Date:   25 January 2026
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

.- ARTIFICIAL INTELLIGENCE & DATA ANALYTICS. .- The Psychology of Video Resolution Choices of Counter-Strike Professional Players and its Impact on their Ratings. .- A Simple Review of Artificial Intelligence and Machine Learning  Applications in Petroleum Engineering. .- Improving Medicinal Plant Identification with Grayscale and Canny Edge Detection. .- Real-Time Traffic Analytics and Control for City Street. .- Image-Based Anthropometric Measurement System Using Pose Estimation. .- SignLangTech: Transforming Sign Language into Real-Time Communication with CNNs. .- Driving Towards Efficiency: Leveraging GCP Services for Data Analytics to Enhance Uber's Ride-sharing Experience and Operational Strategies. .- Digital Footprints and Women’s Protection: Crime and Harassment Metrics in Indian Urban Regions. .- AI and Big Data Analytics in Healthcare: Current Applications and Future Trends. .- QuiltCraft: A Computer Vision Framework for Sustainable Upcycling Waste Textiles into Artistic Quilts. .- Automatic Fraud insurance claim detection system. .- DEEP LEARNING. .- Classification of Alzheimer's Disease through Deep Learn-ing Approaches with Contextual and Inter- Channel Fea-tures from Brain MRI. .- Early Prediction of Alzheimer's Disease using Deep Learning Models. .- Emotion Recognition in Text and Images Using Deep Learning. .- Applying Inception-V3 for Skin Disease Classification: A Deep Learning Approach Using the ISIC Dataset. .- Real-Time Text Prediction and Speech Synthesis for Accessibility: A Bidirectional LSTM Approach. .- Examining and contrasting deep learning methods for DNA sequence classification in order to predict cancer mutations in India. .- Building Resilience: Crafting a Deep Learning-based Comment Toxicity Model in Python to Foster Safer Online Communities. .- AngioResUNet++: A Transfer Learning-Based Deep Neural Network for Precise Segmentation and Classification of Coronary Arteries in CCTA Images. .- Advanced Fake News Detection on Social Media: Leveraging Geometric Deep Learning and Propagation Pattern. .- Deep Learning for Image Inpainting: Leveraging Partial Convolutions. .- Enhancing Real-Time Object Detection and Recognition: A Hybrid BP-LSTM Deep Learning Approach for Advanced Computer Vision Systems. .- Sea Creature Classification Using Convolutional Neural Networks. .- Advanced Speaker Recognition Using Traditional Machine Learning and LSTM: A Performance Evaluation Across Multiple Datasets. .- AI-driven system for chronic wound assessment: an automated approach using U-Net architecture for foot ulcers in CKD patients. .- Advancements in Brain Tumor Classification: Unveiling the Power of CNN-SVM Fusion for MRI Datasets. .- Improved Deepfake Detection In Videos Through Green Channel Conversion and Performance Analysis of Activation  Functions. .- Early Prognosis of Post-Covid Cardiovascular Disease With Clinical Data And Chest X-Ray Image Using Hybrid Transformer-Based Approach. .- Malware Variant Traffic Identification at an IoT Edge Gateway using QDCNN with Optimization.

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