Neural Information Processing [electronic resource] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part III / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu.
Contributor(s): Hirose, Akira [editor.] | Ozawa, Seiichi [editor.] | Doya, Kenji [editor.] | Ikeda, Kazushi [editor.] | Lee, Minho [editor.] | Liu, Derong [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 9949Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: XVIII, 651 p. 215 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319466750.Subject(s): Computer science | Computers | Data mining | Artificial intelligence | Image processing | Pattern recognition | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Artificial Intelligence (incl. Robotics) | Computation by Abstract Devices | Data Mining and Knowledge Discovery | Information Systems Applications (incl. Internet)Additional physical formats: Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
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Springer eBooksSummary: 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.
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.
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