Neural Information Processing 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part III /

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 submiss...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Hirose, Akira (Editor ), Ozawa, Seiichi (Editor ), Doya, Kenji (Editor ), Ikeda, Kazushi (Editor ), Lee, Minho (Editor ), Liu, Derong (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Theoretical Computer Science and General Issues, 9949
Temas:
Pattern recognition systems.
Computer vision.
Artificial intelligence.
Computer science.
Data mining.
Application software.
Automated Pattern Recognition.
Computer Vision.
Artificial Intelligence.
Theory of Computation.
Data Mining and Knowledge Discovery.
Computer and Information Systems Applications.
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:XVIII, 651 p. 215 illus. online resource.
ISBN:9783319466750
ISSN:2512-2029 ;

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