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Detection and Identification of Rare Audio-visual Cues (Hardcover, 2012) Loot Price: R2,938
Discovery Miles 29 380
Detection and Identification of Rare Audio-visual Cues (Hardcover, 2012): Daphna Weinshall, Joern Anemuller, Luc Van Gool

Detection and Identification of Rare Audio-visual Cues (Hardcover, 2012)

Daphna Weinshall, Joern Anemuller, Luc Van Gool

Series: Studies in Computational Intelligence, 384

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Loot Price R2,938 Discovery Miles 29 380 | Repayment Terms: R275 pm x 12*

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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."

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Studies in Computational Intelligence, 384
Release date: October 2011
First published: 2012
Editors: Daphna Weinshall • Joern Anemuller • Luc Van Gool
Dimensions: 235 x 155 x 13mm (L x W x T)
Format: Hardcover - Cloth over boards
Pages: 192
Edition: 2012
ISBN-13: 978-3-642-24033-1
Categories: Books > Computing & IT > Computer software packages > Multimedia
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 3-642-24033-X
Barcode: 9783642240331

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