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020 _a9783319111797
_9978-3-319-11179-7
024 7 _a10.1007/978-3-319-11179-7
_2doi
035 _ato000544041
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aArtificial Neural Networks and Machine Learning – ICANN 2014
_helectronic resource
_b24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings /
_cedited by Stefan Wermter, Cornelius Weber, Włodzisław Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Alessandro E. P. Villa.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXV, 852 p. 338 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8681
505 0 _aRecurrent Networks -- Sequence Learning -- Echo State Networks -- Recurrent Network Theory -- Competitive Learning and Self-Organisation.- Clustering and Classification -- Trees and Graphs -- Human-Machine Interaction -- Deep Networks.- Theory -- Optimization -- Layered Networks -- Reinforcement Learning and Action -- Vision -- Detection and Recognition -- Invariances and Shape Recovery -- Attention and Pose Estimation -- Supervised Learning -- Ensembles -- Regression -- Classification -- Dynamical Models and Time Series -- Neuroscience -- Cortical Models -- Line Attractors and Neural Fields -- Spiking and Single Cell Models -- Applications -- Users and Social Technologies -- Demonstrations.
520 _aThe book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.
650 0 _aComputer Science.
_9155490
650 0 _aComputer software.
_9303280
650 0 _aArtificial intelligence.
_9274099
650 0 _aComputer vision.
_9274100
650 0 _aOptical pattern recognition.
_9304126
650 1 4 _aComputer Science.
_9155490
650 2 4 _aArtificial Intelligence (incl. Robotics).
_9274102
650 2 4 _aComputation by Abstract Devices.
_9305111
650 2 4 _aAlgorithm Analysis and Problem Complexity.
_9303732
650 2 4 _aPattern Recognition.
_9304129
650 2 4 _aInformation Systems Applications (incl. Internet).
_9299051
650 2 4 _aImage Processing and Computer Vision.
_9303601
700 1 _aWermter, Stefan.
_eeditor.
_9322386
700 1 _aWeber, Cornelius.
_eeditor.
_9451700
700 1 _aDuch, Włodzisław
_eeditor.
_991580
700 1 _aHonkela, Timo.
_eeditor.
_9451701
700 1 _aKoprinkova-Hristova, Petia.
_eeditor.
_9414901
700 1 _aMagg, Sven.
_eeditor.
_9451702
700 1 _aPalm, Günther.
_eeditor.
_9322385
700 1 _aVilla, Alessandro E. P.
_eeditor.
_9414902
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aLecture Notes in Computer Science,
_9279505
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-11179-7
912 _aZDB-2-SCS
912 _aZDB-2-LNC
999 _c401997