Weakly supervised methods for learning actions and objects: Reducing human intervention in learning visual concepts for Artificial Intelligence - Couverture souple

Prest, Alessandro

 
9783659327544: Weakly supervised methods for learning actions and objects: Reducing human intervention in learning visual concepts for Artificial Intelligence
Couverture souple
ISBN 10 : 3659327549 ISBN 13 : 9783659327544
Editeur : LAP LAMBERT Academic Publishing, 2013

Synopsis

The past decade will be remembered as one of maturity for Artificial Intelligence (AI). Successful applications such as Google Goggles, Siri, IBM Watson have positively impacted people’s everyday life. These systems are able to interpret in real-time highly complex natural signals, in the form of text, audio or video data: a task thought the exclusive domain of human intelligence before the two-thousands. This book discusses methods of computer vision, a branch of AI where the input for the system is represented by images and videos depicting visual scenes. Most computer vision tasks have the objective of recognizing visual concepts such as the presence of a particular object or the occurrence of a specific event in the input data. These systems learn visual concepts through examples (i.e. images) which have been manually annotated by humans. While this paradigm allowed the field to tremendously progress in the last decade, it has now become one of its major bottlenecks. This work tap into the wealth of visual data available on the net and presents methods able to exploit this information to learn visual concepts without the need of major human annotation effort.

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Présentation de l'éditeur

The past decade will be remembered as one of maturity for Artificial Intelligence (AI). Successful applications such as Google Goggles, Siri, IBM Watson have positively impacted people’s everyday life. These systems are able to interpret in real-time highly complex natural signals, in the form of text, audio or video data: a task thought the exclusive domain of human intelligence before the two-thousands. This book discusses methods of computer vision, a branch of AI where the input for the system is represented by images and videos depicting visual scenes. Most computer vision tasks have the objective of recognizing visual concepts such as the presence of a particular object or the occurrence of a specific event in the input data. These systems learn visual concepts through examples (i.e. images) which have been manually annotated by humans. While this paradigm allowed the field to tremendously progress in the last decade, it has now become one of its major bottlenecks. This work tap into the wealth of visual data available on the net and presents methods able to exploit this information to learn visual concepts without the need of major human annotation effort.

Biographie de l'auteur

Alessandro Prest is co-founder of several ventures, where he helps delivering Artificial Intelligence solutions to different markets.In the past he has covered several research positions in different institutions. He received a Ph.D. in Artificial Intelligence from ETH Zurich in 2012.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2013
Langue
anglais
ISBN 10 
3659327549
ISBN 13 
9783659327544
Reliure
Broché
Nombre de pages
128
Coordonnées du fabricant
non disponible
Personne responsable
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