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ISBN: 9783642240348
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Daphna Weinshall; Jörn Anemüller; Luc Van Gool:
Detection and Identification of Rare Audio-visual Cues - nouveau livre2011, ISBN: 9783642240348
eBooks, eBook Download (PDF), 2012, Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later… Plus…
2010
ISBN: 9783642240348
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to … Plus…
ISBN: 9783642240348
This volume brings together researchers from different disciplines to discuss new approaches for identifying, and reacting to, unexpected events in information-rich environments. COMPUTER… Plus…
2011, ISBN: 9783642240348
eBooks, eBook Download (PDF), 2012, [PU: Springer Berlin], Springer Berlin, 2011
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Informations détaillées sur le livre - Detection and Identification of Rare Audio-visual Cues
EAN (ISBN-13): 9783642240348
ISBN (ISBN-10): 3642240348
Date de parution: 2011
Editeur: Springer Berlin
192 Pages
Langue: eng/Englisch
Livre dans la base de données depuis 2012-10-24T21:09:35+02:00 (Zurich)
Page de détail modifiée en dernier sur 2024-01-24T20:06:06+01:00 (Zurich)
ISBN/EAN: 9783642240348
ISBN - Autres types d'écriture:
3-642-24034-8, 978-3-642-24034-8
Autres types d'écriture et termes associés:
Auteur du livre: wein, anemüller, van gool
Titre du livre: visual, cues, identification
Données de l'éditeur
Auteur: Daphna Weinshall; Jörn Anemüller; Luc van Gool
Titre: Studies in Computational Intelligence; Detection and Identification of Rare Audio-visual Cues
Editeur: Springer; Springer Berlin
192 Pages
Date de parution: 2011-11-23
Berlin; Heidelberg; DE
Langue: Anglais
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
VIII, 192 p.
EA; E107; eBook; Nonbooks, PBS / Technik/Allgemeines, Lexika; Künstliche Intelligenz; Verstehen; Computational Intelligence; Detection of Rare Audiovisual Cues; Identification of Rare Audiovisual Cues; Machine Learning; B; Computational Intelligence; Artificial Intelligence; Multimedia Information Systems; Engineering; Grafische und digitale Media-Anwendungen; BC
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to estimate the current state of the world. An implied assumption is that the future is stochastically similar to the past. The approach fails when the system encounters situations that are not anticipated from the past experience. In contrast, successful natural organisms identify new unanticipated stimuli and situations and frequently generate appropriate responses. The observation described above lead to the initiation of the DIRAC EC project in 2006. In 2010 a workshop was held, aimed to bring together researchers and students from different disciplines in order to present and discuss new approaches for identifying and reacting to unexpected events in information-rich environments. This book includes a summary of the achievements of the DIRAC project in chapter 1, and a collection of the papers presented in this workshop in the remaining parts.Recent research in Detection and Identification of Rare Audiovisual Cues Scientific outcome of the European project DIRAC (Detection and Identification of Rare Audio-visual Cues) Written by leading experts in the field
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