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Artificial neural networks and machine learning-- ICANN 2014 [electronic resource] : 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings / Stefan Wermter ... [and more] (eds.).

International Conference on Artificial Neural Networks (European Neural Network Society) (24th : 2014 : Hamburg, Germany); Wermter, Stefan, editor.
2014
QA76.87
Available Online
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Title
Artificial neural networks and machine learning-- ICANN 2014 [electronic resource] : 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014. Proceedings / Stefan Wermter ... [and more] (eds.).
Meeting Name
International Conference on Artificial Neural Networks (European Neural Network Society) (24th : 2014 : Hamburg, Germany)
ISBN
9783319111797 electronic book
3319111795 electronic book
9783319111780
DOI
https://doi.org/10.1007/978-3-319-11179-7
Published
Cham : Springer, 2014.
Language
English
Description
1 online resource (xxvi, 852 pages) : illustrations.
Item Number
10.1007/978-3-319-11179-7 doi
Call Number
QA76.87
Dewey Decimal Classification
006.3/2
Summary
The 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.
Note
International conference proceedings.
Includes author index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed August 27, 2014).
Added Author
Wermter, Stefan, editor.
Series
Lecture notes in computer science ; 8681.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
Available in Other Form
Print version: 9783319111780
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Recurrent 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.

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