Neural Information Processing : 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings. Part V /

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Bibliographic Details
Meeting name:ICONIP (Conference) (27th : 2020 : Bangkok, Thailand)
Imprint:Cham : Springer, 2020.
Description:1 online resource (xxix, 844 pages) : illustrations (some color)
Language:English
Series:Communications in Computer and Information Science, 1865-0929 ; 1333
Communications in computer and information science ; 1333.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12609425
Hidden Bibliographic Details
Other authors / contributors:Chan, Jonathan H., editor
King, Irwin, 1961-
Kwok, James (Professor of Computer Science and Engineering), editor
Leung, Chi Sing, editor
Pasupa, Kitsuchart, editor
Yang, Haiqin, editor
ISBN:9783030638238
3030638235
9783030638221
Digital file characteristics:text file
PDF
Summary:The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.* For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.
Other form:Printed edition: 9783030638221
Printed edition: 9783030638245
Standard no.:10.1007/978-3-030-63823-8
Table of Contents:
  • Computational Intelligence
  • Machine Learning
  • Neural Network Models
  • Robotics and Control
  • Time Series Analysis.