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Intelligent Data Engineering and Automated Learning – IDEAL 2023 24th International Conference, Évora, Portugal, November 22–24, 2023, Proceedings /

This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from...

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Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Quaresma, Paulo (Editor), Camacho, David (Editor), Yin, Hujun (Editor), Gonçalves, Teresa (Editor), Julian, Vicente (Editor), Tallón-Ballesteros, Antonio J. (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Udgivelse:1st ed. 2023.
Serier:Lecture Notes in Computer Science, 14404
Fag:
Data mining.
Machine learning.
Software engineering.
Education > Data processing.
Computer vision.
Data Mining and Knowledge Discovery.
Machine Learning.
Software Engineering.
Computers and Education.
Computer Vision.
Online adgang:https://doi.org/10.1007/978-3-031-48232-8
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Beskrivelse
Summary:This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.
Fysisk beskrivelse:1 online resource (XVII, 549 p. 173 illus.). 152 illus. in color.
ISBN:9783031482328
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-48232-8

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