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161005 ||| eng |
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|a 9783319466811
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|a Hirose, Akira
|e [editor]
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|a Neural Information Processing
|h Elektronische Ressource
|b 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV
|c edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu
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| 250 |
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|a 1st ed. 2016
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2016, 2016
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| 300 |
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|a XIX, 663 p. 254 illus
|b online resource
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| 653 |
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|a Computer science
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| 653 |
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|a Computer vision
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Computer Vision
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Theory of Computation
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| 653 |
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|a Automated Pattern Recognition
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| 653 |
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|a Pattern recognition systems
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| 700 |
1 |
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|a Ozawa, Seiichi
|e [editor]
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| 700 |
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|a Doya, Kenji
|e [editor]
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| 700 |
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|a Ikeda, Kazushi
|e [editor]
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Theoretical Computer Science and General Issues
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| 028 |
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|a 10.1007/978-3-319-46681-1
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|u https://doi.org/10.1007/978-3-319-46681-1?nosfx=y
|x Verlag
|3 Volltext
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|a 006.4
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|a 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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