Computing and Machine Learning : Proceedings of CML 2024, Volume 3 (Lecture Notes in Networks and Systems) （2025）

Bansal, Jagdish Chand (EDT)/ Borah, Samarjeet (EDT)/ Hussain, Shahid (EDT)

Springer Nature（2024/12発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 484 p.
• 言語 ENG
• 商品コード 9789819775484

Full Description

This book features high-quality research papers presented at the International Conference on Computing and Machine Learning (CML 2024), organized by Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India during April 29-30, 2024. The book presents diverse range of topics, including machine learning algorithms and models, deep learning and neural networks, computer vision and image processing, natural language processing, robotics and automation, reinforcement learning, big data analytics, cloud computing, internet of things, human-robot interaction, ethical and social implications of AI, applications in healthcare, finance, and industry, computer modeling, quantum computing, high-performance computing, cognitive and parallel computing, cloud computing, distributed computing, embedded computing, human-centered computing and mobile computing.

Contents

Scaling Insights: Unleashing the Power of Scalable Clustering Indices for Big Data Exploration.- Prediction of Chronic Respiratory Diseases using Machine Learning Algorithms.- Experimental Evaluation of Scalable Database Architectures for High-Performance Applications.- Multi-class Semantic Segmentation: a Deep Supervised Approach For Brain Tumor Detection Using 3D U-Net++ Architecture.- DeepSeg: A Decision Support System for Enhanced Segmentation of Human Tissue Image.- Transcription-Based on Pitches an Ontology for the System Knowledge Representation.- A Deep Learning Framework for Paddy and Maize leaf Disease Detection.- An Accurate People Counting System Based on Object Detection and Tracking.- Structural and Functional Features of The Synthetic Benchmark.- Lacunarity-Based Characterization of Hyperspectral Spatial Patterns U-Net Segmentation and Lacunarity for Enhanced Analysis of Hyperspectral Imagery.- Detection of Buried Ieds Using Convolutional Neural Networks on Ground Images from Thermal Cameras Embarked on UAVs.- Smart Decision-Making in The Green Economy: A Fuzzy Logic Approach.- An Integrated Scalable Healthcare Management System Using IOT.