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Trends in sustainable computing and machine intelligenceproceedings of ICTSM 2024 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Trends in sustainable computing and machine intelligenceedited by Surekha Lanka, Antonio Sarasa Cabezuelo, Chandrasekar Vuppalapati.
其他題名:	proceedings of ICTSM 2024 /
其他題名:	ICTSM 2024
其他作者:	Lanka, Surekha.
團體作者:
出版者:	Singapore :Springer Nature Singapore :2025.
面頁冊數:	xiii, 510 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machine learningCongresses.
電子資源:	https://doi.org/10.1007/978-981-96-1452-3
ISBN:	9789819614523$q(electronic bk.)

Trends in sustainable computing and machine intelligenceproceedings of ICTSM 2024 /
Trends in sustainable computing and machine intelligenceproceedings of ICTSM 2024 /[electronic resource] :ICTSM 2024edited by Surekha Lanka, Antonio Sarasa Cabezuelo, Chandrasekar Vuppalapati. - Singapore :Springer Nature Singapore :2025. - xiii, 510 p. :ill., digital ;24 cm. - Algorithms for intelligent systems,2524-7573. - Algorithms for intelligent systems..

This book is a collection of best selected research papers presented at International Conference on Trends in Sustainable Computing and Machine Intelligence (ICTSM 2024) organized by Stamford International University, Bangkok, Thailand, during September 12-13, 2024. The book includes original research by researchers working in the field of machine learning. The book covers important topics like decision support systems, neural networks and applications, machine learning, natural language processing, automated problem solving, AI and evolutionary algorithms, intelligent information systems, computational intelligence, computer vision and image processing, cognitive and biologically inspired vision, soft computing and applications, hybrid intelligent systems, distributed computing, pattern recognition and analysis, ubiquitous and high-performance computing, security, trust and privacy, big data for sustainable computing, and energy-aware machine learning.

ISBN: 9789819614523$q(electronic bk.)

Standard No.: 10.1007/978-981-96-1452-3doiSubjects--Topical Terms:

384498
Machine learning
--Congresses.

LC Class. No.: Q325.5 / .I58 2024

Dewey Class. No.: 006.31

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