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Detection and Identification of Rare Audio-visual Cues (Studies in Computational Intelligence, 384) - Softcover
Synopsis
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.
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From the Back Cover
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.
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Detection and Identification of Rare Audio-visual Cues
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Detection and Identification of Rare Audio-visual Cues (Studies in Computational Intelligence, 384)
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Detection and Identification of Rare Audio-visual Cues (Paperback)
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Paperback. Condition: new. Paperback. 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. Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783642269721
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Detection and Identification of Rare Audio-visual Cues (Studies in Computational Intelligence, 384)
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Detection and Identification of Rare Audio-visual Cues
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Detection and Identification of Rare Audio-visual Cues (Studies in Computational Intelligence, 384)
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Detection and Identification of Rare Audio-visual Cues
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 200 pp. Englisch. Seller Inventory # 9783642269721
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Detection and Identification of Rare Audio-Visual Cues
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Detection and Identification of Rare Audio-visual Cues
Published by
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2013
ISBN 10: 3642269729
ISBN 13: 9783642269721
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Condition: New. This volume brings together researchers from different disciplines to discuss new approaches for identifying, and reacting to, unexpected events in information-rich environments. Editor(s): Weinshall, Daphna; Anemuller, Jorn; Gool, Luc van. Series: Studies in Computational Intelligence. Num Pages: 192 pages, biography. BIC Classification: UG; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 11. Weight in Grams: 314. . 2013. Paperback. . . . . Seller Inventory # V9783642269721
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Detection and Identification of Rare Audio-Visual Cues
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