Intelligent Data Engineering and Automated Learning – IDEAL 2021 by Hujun Yin, David Camacho, Peter Tino, Richard Allmendinger, Antonio J. Tallón-Ballesteros, Ke Tang, Sung-Bae Cho, Paulo Novais & Susana Nascimento

Intelligent Data Engineering and Automated Learning – IDEAL 2021

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  • Genre Computers & Internet
  • Publisher Springer Science & Business Media
  • Released
  • Size 67.73 MB
  • Length 848 Pages

Description

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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