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Artificial Neural Networks and Machine Learning – ICANN 2016 [electronic resource] : 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II / edited by Alessandro E.P. Villa, Paolo Masulli, Antonio Javier Pons Rivero.

Contributor(s): Material type: TextSeries: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016Description: XXIX, 557 p. 173 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319447810
Subject(s): DDC classification:
  • 006.3 23
Online resources:
Contents:
Deep Learning -- Classification and Forecasting -- Recognition and Navigation.
Summary: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume. .
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Deep Learning -- Classification and Forecasting -- Recognition and Navigation.

The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume. .

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