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Neural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 812, 2021, Proceedings, Part VI 1st ed. 2021 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 772 pages, height x width: 235x155 mm, weight: 1211 g, 28 Illustrations, black and white; XXVIII, 772 p. 28 illus., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1517
  • Izdošanas datums: 07-Dec-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030923096
  • ISBN-13: 9783030923099
  • Mīkstie vāki
  • Cena: 109,38 €*
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  • Formāts: Paperback / softback, 772 pages, height x width: 235x155 mm, weight: 1211 g, 28 Illustrations, black and white; XXVIII, 772 p. 28 illus., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1517
  • Izdošanas datums: 07-Dec-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030923096
  • ISBN-13: 9783030923099
The two-volume set CCIS 1516 and 1517 constitutes thoroughly refereed short papers presented at the 28th International Conference on Neural Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. 

The 176 short and workshop papers presented in this volume were carefully reviewed and selected for publication out of 1093 submissions. The papers are organized in topical sections as follows: theory and algorithms; AI and cybersecurity; cognitive neurosciences; human centred computing; advances in deep and shallow machine learning algorithms for biomedical data and imaging; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; applications.

* The conference was held virtually due to the COVID-19 pandemic.

Cognitive Neurosciences.- Human Centred Computing.- Advances in deep and
shallow machine learning algorithms for biomedical data and
imaging.- Reliable, Robust, and Secure Machine Learning Algorithms.- Theory
and Applications of Natural Computing Paradigms.- Applications.