Image Retrieval System: An Indexing Technique Using Annotation for Improved Markovian Model Based Image Retrieval System - Couverture souple

Seenivasan, Sangeetha

9786200287366: Image Retrieval System: An Indexing Technique Using Annotation for Improved Markovian Model Based Image Retrieval System

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ISBN 10 : 6200287368 ISBN 13 : 9786200287366

Editeur : LAP LAMBERT Academic Publishing, 2019

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Online image retrieval system is more important in the real world environment where the users submitted their queries to retrieve the images. The main aim of mining is extracting valuable information from huge volume of textual or image datasets. The user queries are mined to enhance the web searching which is extremely useful to improve the retrieval effectiveness. The image retrieval accuracy is measured based on the user satisfaction level. Automatic annotation is utilized for operating over high dimensional text documents or image contents. Different online image retrieval techniques are available like Latent Semantic Indexing (LSI), Markovian Semantic Indexing (MSI) etc., but these techniques cannot retrieve the images accurately due to the lack of semantic knowledge about the user submitted high level keywords. Moreover the LSI and MSI have less image retrieval accuracy. Hence, this research work focussed on the improvement of the accuracy of the image retrieval system.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2019
Langue: anglais
ISBN 10: 6200287368
ISBN 13: 9786200287366
Reliure: Broch�
Nombre de pages: 112
Coordonn�es du fabricant: non disponible
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Image Retrieval System

Sangeetha Seenivasan

Edit� par LAP LAMBERT Academic Publishing Okt 2019, 2019

ISBN 10 : 6200287368 ISBN 13 : 9786200287366

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Online image retrieval system is more important in the real world environment where the users submitted their queries to retrieve the images. The main aim of mining is extracting valuable information from huge volume of textual or image datasets. The user queries are mined to enhance the web searching which is extremely useful to improve the retrieval effectiveness. The image retrieval accuracy is measured based on the user satisfaction level. Automatic annotation is utilized for operating over high dimensional text documents or image contents. Different online image retrieval techniques are available like Latent Semantic Indexing (LSI), Markovian Semantic Indexing (MSI) etc., but these techniques cannot retrieve the images accurately due to the lack of semantic knowledge about the user submitted high level keywords. Moreover the LSI and MSI have less image retrieval accuracy. Hence, this research work focussed on the improvement of the accuracy of the image retrieval system. 112 pp. Englisch. N� de r�f. du vendeur 9786200287366

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Image Retrieval System

Sangeetha Seenivasan

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Seenivasan SangeethaDr. Sangeetha Seenivasan is Head and Assistant Professor, Department of CA and IT. She has completed her B.Sc (CS)., M.Sc (CT)., M.Phil. and Ph.D. in Bharathiar University. She got Gold Medal on her PG Degree. She. N� de r�f. du vendeur 385887337

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Image Retrieval System

Sangeetha Seenivasan

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Online image retrieval system is more important in the real world environment where the users submitted their queries to retrieve the images. The main aim of mining is extracting valuable information from huge volume of textual or image datasets. The user queries are mined to enhance the web searching which is extremely useful to improve the retrieval effectiveness. The image retrieval accuracy is measured based on the user satisfaction level. Automatic annotation is utilized for operating over high dimensional text documents or image contents. Different online image retrieval techniques are available like Latent Semantic Indexing (LSI), Markovian Semantic Indexing (MSI) etc., but these techniques cannot retrieve the images accurately due to the lack of semantic knowledge about the user submitted high level keywords. Moreover the LSI and MSI have less image retrieval accuracy. Hence, this research work focussed on the improvement of the accuracy of the image retrieval system.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 112 pp. Englisch. N� de r�f. du vendeur 9786200287366

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Image Retrieval System : An Indexing Technique Using Annotation for Improved Markovian Model Based Image Retrieval System

Sangeetha Seenivasan

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6200287368 ISBN 13 : 9786200287366

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Online image retrieval system is more important in the real world environment where the users submitted their queries to retrieve the images. The main aim of mining is extracting valuable information from huge volume of textual or image datasets. The user queries are mined to enhance the web searching which is extremely useful to improve the retrieval effectiveness. The image retrieval accuracy is measured based on the user satisfaction level. Automatic annotation is utilized for operating over high dimensional text documents or image contents. Different online image retrieval techniques are available like Latent Semantic Indexing (LSI), Markovian Semantic Indexing (MSI) etc., but these techniques cannot retrieve the images accurately due to the lack of semantic knowledge about the user submitted high level keywords. Moreover the LSI and MSI have less image retrieval accuracy. Hence, this research work focussed on the improvement of the accuracy of the image retrieval system. N� de r�f. du vendeur 9786200287366

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