Artificial Neural Networks and Machine Learning - ICANN 2011 [electronic resource] : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II / edited by Timo Honkela, Włodzisław Duch, Mark Girolami, Samuel Kaski.
Contributor(s): Honkela, Timo [editor.]
| Duch, Włodzisław [editor.] | Girolami, Mark [editor.] | Kaski, Samuel [editor.] | SpringerLink (Online service).
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BookSeries: Theoretical Computer Science and General Issues: 6792Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Edition: 1st ed. 2011.Description: XXII, 474 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642217388.Subject(s): Artificial intelligence | Computer science | Algorithms | Pattern recognition systems | Application software | Computer vision | Artificial Intelligence | Theory of Computation | Algorithms | Automated Pattern Recognition | Computer and Information Systems Applications | Computer VisionAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.
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This two volume set (LNCS 6791 and LNCS 6792) constitutes the refereed proceedings of the 21th International Conference on Artificial Neural Networks, ICANN 2011, held in Espoo, Finland, in June 2011. The 106 revised full or poster papers presented were carefully reviewed and selected from numerous submissions. ICANN 2011 had two basic tracks: brain-inspired computing and machine learning research, with strong cross-disciplinary interactions and applications.
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