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Titlebook: Machine Intelligence, Tools, and Applications; Proceedings of the I Satchidananda Dehuri,Sung-Bae Cho,Ashish Ghosh Conference proceedings 2

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书目名称Machine Intelligence, Tools, and Applications
副标题Proceedings of the I
编辑Satchidananda Dehuri,Sung-Bae Cho,Ashish Ghosh
视频video
概述Presents recent research in Machine Intelligence.Is the proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2023.Written by experts in the field
丛书名称Learning and Analytics in Intelligent Systems
图书封面Titlebook: Machine Intelligence, Tools, and Applications; Proceedings of the I Satchidananda Dehuri,Sung-Bae Cho,Ashish Ghosh Conference proceedings 2
描述.This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications..
出版日期Conference proceedings 2024
关键词Computational Intelligence; Machine Intelligence; Computer Vision; Image Processing Solutions; Multimedi
版次1
doihttps://doi.org/10.1007/978-3-031-65392-6
isbn_softcover978-3-031-65394-0
isbn_ebook978-3-031-65392-6Series ISSN 2662-3447 Series E-ISSN 2662-3455
issn_series 2662-3447
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Multifaceted Analysis of Climate Trends and Air Quality in Indian Metropolises: A Machine Learning raging over three decades of data. Employing a fusion of machine learning techniques like Gradient Boosting and traditional methods such as ARIMA, we scrutinize the interplay of urbanization, climate shifts, and pollution levels. Through extensive data pre-processing, feature engineering, and model
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Implementation and Optimization of Swarm Based System for Multi-agent Coordination and Task Executiocusing on the crucial task of oil spill remediation. The study involves designing and refining swarm-based robotic systems for coordinated multi-agent operations in the demanding conditions of marine environments. The maneuverability and overall operational performance of autonomous robotic swarms
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