Neural Information Processing : 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part I /

The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22-26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and select...

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Bibliographic Details
Corporate Author:	SpringerLink (Online service)
Other Authors:	Tanveer, Mohammad (Editor), Agarwal, Sonali (Editor), Ozawa, Seiichi (Editor), Ekbal, Asif (Editor), Jatowt, Adam (Editor)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2023.
Edition:	1st ed. 2023.
Series:	Lecture Notes in Computer Science, 13623
Subjects:	Pattern recognition systems. Data mining. Machine learning. Social sciences-Data processing. Automated Pattern Recognition. Data Mining and Knowledge Discovery. Machine Learning. Computer Application in Social and Behavioral Sciences. Electronic books.
Online Access:	Connect to the full text of this electronic book

Description
Summary:	The three-volume set LNCS 13623, 13624, and 13625 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22-26, 2022. The 146 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.
Physical Description:	1 online resource (XXXV, 627 pages 172 illustrations, 162 illustrations in color.)
ISBN:	9783031301056
ISSN:	1611-3349 ;
DOI:	10.1007/978-3-031-30105-6