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020 _a9783319466729
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024 7 _a10.1007/978-3-319-46672-9
_2doi
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050 4 _aTK7882.P3
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_2bicssc
072 7 _aCOM016000
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072 7 _aUYQP
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082 0 4 _a006.4
_223
245 1 0 _aNeural Information Processing
_h[electronic resource] :
_b23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16-21, 2016, Proceedings, Part II /
_cedited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIX, 739 p. 252 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v9948
505 0 _aDeep 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.
520 _aThe 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. .
650 0 _aPattern recognition systems.
_93953
650 0 _aComputer vision.
_9155002
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer science.
_99832
650 0 _aData mining.
_93907
650 0 _aApplication software.
_9155003
650 1 4 _aAutomated Pattern Recognition.
_931568
650 2 4 _aComputer Vision.
_9155004
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aTheory of Computation.
_9155005
650 2 4 _aData Mining and Knowledge Discovery.
_9155006
650 2 4 _aComputer and Information Systems Applications.
_9155007
700 1 _aHirose, Akira.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9155008
700 1 _aOzawa, Seiichi.
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_9155009
700 1 _aDoya, Kenji.
_eeditor.
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_9155010
700 1 _aIkeda, Kazushi.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9155011
700 1 _aLee, Minho.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9155012
700 1 _aLiu, Derong.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9155013
710 2 _aSpringerLink (Online service)
_9155014
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aTheoretical Computer Science and General Issues,
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_v9948
_9155015
856 4 0 _uhttps://doi.org/10.1007/978-3-319-46672-9
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