weinshall daphna (22 resultados)

Condición: As New. Unread book in perfect condition.

Condición: New. In.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. In.

Paperback. Condición: Brand New. 2012 edition. 200 pages. 9.25x6.10x0.46 inches. In Stock.

Hardcover. Condición: Brand New. 2012 edition. 200 pages. 9.00x6.25x0.50 inches. In Stock.

Taschenbuch. Condición: Neu. Detection and Identification of Rare Audio-visual Cues | Daphna Weinshall (u. a.) | Taschenbuch | viii | Englisch | 2013 | Springer | EAN 9783642269721 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Condición: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 200 pp. Englisch.

Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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. .

Paperback. Condición: Like New. Like New. book.

Condición: new. Questo è un articolo print on demand.

Condición: new. Questo è un articolo print on demand.

Taschenbuch. Condición: 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.

Buch. Condición: 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.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 fieldMachine .

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 fieldMachine .

Buch. Condición: Neu. Detection and Identification of Rare Audio-visual Cues | Daphna Weinshall (u. a.) | Buch | viii | Englisch | 2011 | Springer | EAN 9783642240331 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 200 pp. Englisch.