Narrowing Down the Semantic Gap between Content and Context: Using Multimodal Image Keywords - Couverture souple
Synopsis
Conventional information retrieval is based solely on text, and the approaches to textual information retrieval have been transplanted into image retrieval in a variety of ways, including the representation of an image as a vector of feature values of different modalities. It has been widely recognized that the image retrieval techniques should become an integration of different modalities, such as color, texture and associated text keywords. To take the cue from text-based retrieval techniques, we construct “visual keywords” using vector quantization of small sized image tiles. Both visual and text keywords are combined and used to represent an image as a single multimodal vector. We demonstrate the power of these multimodal image keywords for clustering and retrieval of relevant images from a large collection.
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À propos de l?auteur
Dr. Rajeev Agrawal is working at North Carolina A & T State University, USA. His current research focuses on Anomaly Detection in Computer Network, Healthcare Fraud Detection, and Content-based Image Retrieval. He has published 30 referred journal and conference papers, and 4 book chapters. He is a member of IEEE, ACM, and ASEE.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Narrowing Down the Semantic Gap between Content and Context
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LAP LAMBERT Academic Publishing Okt 2011, 2011
ISBN 10 : 3846520586
ISBN 13 : 9783846520581
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Conventional information retrieval is based solely on text, and the approaches to textual information retrieval have been transplanted into image retrieval in a variety of ways, including the representation of an image as a vector of feature values of different modalities. It has been widely recognized that the image retrieval techniques should become an integration of different modalities, such as color, texture and associated text keywords. To take the cue from text-based retrieval techniques, we construct visual keywords using vector quantization of small sized image tiles. Both visual and text keywords are combined and used to represent an image as a single multimodal vector. We demonstrate the power of these multimodal image keywords for clustering and retrieval of relevant images from a large collection. 136 pp. Englisch. N° de réf. du vendeur 9783846520581
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Narrowing Down the Semantic Gap between Content and Context
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LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3846520586
ISBN 13 : 9783846520581
Neuf
Couverture souple
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Agrawal RajeevDr. Rajeev Agrawal is working at North Carolina A & T State University, USA. His current research focuses on Anomaly Detection in Computer Network, Healthcare Fraud Detection, and Content-based Image Retrieval. He has p. N° de réf. du vendeur 5496331
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Narrowing Down the Semantic Gap between Content and Context
Edité par
LAP LAMBERT Academic Publishing Okt 2011, 2011
ISBN 10 : 3846520586
ISBN 13 : 9783846520581
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Conventional information retrieval is based solely on text, and the approaches to textual information retrieval have been transplanted into image retrieval in a variety of ways, including the representation of an image as a vector of feature values of different modalities. It has been widely recognized that the image retrieval techniques should become an integration of different modalities, such as color, texture and associated text keywords. To take the cue from text-based retrieval techniques, we construct 'visual keywords' using vector quantization of small sized image tiles. Both visual and text keywords are combined and used to represent an image as a single multimodal vector. We demonstrate the power of these multimodal image keywords for clustering and retrieval of relevant images from a large collection.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Englisch. N° de réf. du vendeur 9783846520581
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Narrowing Down the Semantic Gap between Content and Context : Using Multimodal Image Keywords
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3846520586
ISBN 13 : 9783846520581
Neuf
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Conventional information retrieval is based solely on text, and the approaches to textual information retrieval have been transplanted into image retrieval in a variety of ways, including the representation of an image as a vector of feature values of different modalities. It has been widely recognized that the image retrieval techniques should become an integration of different modalities, such as color, texture and associated text keywords. To take the cue from text-based retrieval techniques, we construct visual keywords using vector quantization of small sized image tiles. Both visual and text keywords are combined and used to represent an image as a single multimodal vector. We demonstrate the power of these multimodal image keywords for clustering and retrieval of relevant images from a large collection. N° de réf. du vendeur 9783846520581
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Narrowing Down the Semantic Gap between Content and Context | Using Multimodal Image Keywords
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3846520586
ISBN 13 : 9783846520581
Neuf
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Taschenbuch. Etat : Neu. Narrowing Down the Semantic Gap between Content and Context | Using Multimodal Image Keywords | Rajeev Agrawal (u. a.) | Taschenbuch | 136 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846520581 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106763662
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