Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Artificial Neural Networks and Machine Learning -- ICANN 2014

24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings
BuchKartoniert, Paperback
852 Seiten
Englisch
Springererschienen am22.09.20142014
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;mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR53,49
E-BookPDF1 - PDF WatermarkE-Book
EUR53,49

Produkt

KlappentextThe 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;
Details
ISBN/GTIN978-3-319-11178-0
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2014
Erscheinungsdatum22.09.2014
Auflage2014
ReiheTheoretical Computer Science and General Issues
Seiten852 Seiten
SpracheEnglisch
Gewicht1306 g
IllustrationenXXV, 852 p. 338 illus.
Artikel-Nr.32592115

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Schlagworte

Autor