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Neural Information Processing [electronic resource] : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part II / 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).
Material type: materialTypeLabelBookSeries: Theoretical Computer Science and General Issues: 9948Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XIX, 739 p. 252 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319466729.Subject(s): 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 ApplicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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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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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