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Neural Information Processing: 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 1621, 2016, Proceedings, Part IV 1st ed. 2016 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 663 pages, height x width: 235x155 mm, 254 Illustrations, black and white; XIX, 663 p. 254 illus., 1 Paperback / softback
  • Sērija : Theoretical Computer Science and General Issues 9950
  • Izdošanas datums: 30-Sep-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319466801
  • ISBN-13: 9783319466804
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  • Cena: 58,86 €
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Neural Information Processing: 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 1621, 2016, Proceedings, Part IV 1st ed. 2016Palielināt
  • Formāts: Paperback / softback, 663 pages, height x width: 235x155 mm, 254 Illustrations, black and white; XIX, 663 p. 254 illus., 1 Paperback / softback
  • Sērija : Theoretical Computer Science and General Issues 9950
  • Izdošanas datums: 30-Sep-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319466801
  • ISBN-13: 9783319466804
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783319466804.html
Keywords:

The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.

Deep and reinforcement learning.- Big data analysis.- Neural data analysis.-Robotics and control.- Bio-inspired/energy efficient information processing.-Whole brain architecture.- Neurodynamics.- Bioinformatics.- Biomedical engineering.- Data mining and cybersecurity workshop.- Machine learning.-Neuromorphic hardware.- Sensory perception.- Pattern recognition.- Social networks.- Brain-machine interface.- Computer vision.- Time series analysis.-Data-driven approach for extracting latent features.- Topological and graph based clustering methods.- Computational intelligence.- Data mining.- Deep neural networks.- Computational and cognitive neurosciences.- Theory and algorithms.