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Intelligent Data Engineering and Automated Learning - IDEAL 2021

22nd International Conference, IDEAL 2021, Manchester, UK, November 25-27, 2021, Proceedings

Language EnglishEnglish
E-book Adobe ePub DRM
E-book Intelligent Data Engineering and Automated Learning - IDEAL 2021 Hujun Yin
Libristo code: 41016913
Publishers Springer, November 2021
This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent D... Full description
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This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic.The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.

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About the book

Full name Intelligent Data Engineering and Automated Learning - IDEAL 2021
Author Hujun Yin, David Camacho, Peter Tino, Richard Allmendinger, Antonio J. Tallon-Ballesteros, Ke Tang, Sung-Bae Cho, Paulo Novais, Susana Nascimento
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2021
EAN 9783030916084
Libristo code 41016913
Publishers Springer

Categories

Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Society & Social Sciences > Education > Educational equipment & technology, computer-aided learning (CAL)
Computing & Information Technology > Computer programming / software engineering > Software Engineering
Computing & Information Technology > Databases > Data mining
Computing & Information Technology > Computer science > Image processing
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