Artificial Neural Networks and Machine Learning -- ICANN 2014 - 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings

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.

List of contents

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.

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.

Product details

• Assisted by: Wlodzislaw Duch (Editor), Wlodzislaw Duch et al (Editor), Timo Honkela (Editor), Petia Koprinkova-Hristova (Editor), Sven Magg (Editor), Günther Palm (Editor), Allessandro E. P Villa (Editor), Allessandro E. P. Villa (Editor), Allessandro E.P. Villa (Editor), Corneliu Weber (Editor), Cornelius Weber (Editor), Stefan Wermter (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2014
• EAN: 9783319111780
• ISBN: 978-3-31-911178-0
• No. of pages: 852
• Dimensions: 163 mm x 241 mm x 42 mm
• Weight: 1306 g
• Illustrations: XXV, 852 p. 338 illus.
• Series: Lecture Notes in Computer Science; Theoretical Computer Science and General Issues; Lecture Notes in Computer Science / Theoretical Computer Science and General Issues; Lecture Notes in Computer Science; Theoretical Computer Science and General Issues
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT