Intelligent Data Engineering and Automated Learning - IDEAL 2021 - 22nd International Conference, IDEAL 2021, Manchester, UK, November 25-27, 2021, Proceedings (Paperback, 1st ed. 2021)


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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Product 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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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Information Systems and Applications, incl. Internet/Web, and HCI, 13113

Release date

November 2021

Availability

Expected to ship within 10 - 15 working days

First published

2021

Editors

, , , , , , , ,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

649

Edition

1st ed. 2021

ISBN-13

978-3-03-091607-7

Barcode

9783030916077

Categories

LSN

3-03-091607-3



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