Proposed New Algorithm Analysis by Devaraj Saravanan (13 results)

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Paperback. Condition: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.

Paperback. Condition: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.

Taschenbuch. Condition: Neu. A Proposed New Algorithm for analysis of Hierarchical Clustering | Saravanan Devaraj | Taschenbuch | 52 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330033948 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recently many applications have been created for categorizing, indexing and retrieving the digital video contents. These applications are used to handle a large quantity of video contents. Due to the restricted man-power, it is much required to develop retrieval methods that automatically extract features from videos and makes use of it. It is a good deal expected to build up the retrieval methods that use the features automatically extracted from videos. These features are nothing but the representation of physical contents such as motion, edge, color etc. The retrieval methods need information of how to integrate/use features for retrieving the exact videos according to the user query.This book further discusses about the basics of indexing, clustering and data mining in the video database. 52 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Video clustering is one of the important task in video data mining. We discuss about the different video clustering techniques using hierarchical clustering algorithms like CURE, BIRCH, CHAMLEON. Set of video frames are clustered using the hierarchical clustering algorithms. As a result of comparison of results all the hierarchical algorithms offer good performance for some set of video files only. That is each clustering algorithm shows best clustering on particular video files only. It fails to forms best clusters of all type of video files. Hence we propose a hierarchical clustering algorithm that offers best clustering performance for all type of video files at any circumstances 52 pp. Englisch.

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Devaraj SaravananD. Saravanan currently working as Associate Professor in the department of Operations & IT, IFHE University,Hyderabad. His areas of interest are image processing, data mining, DBMS, Business Analytics, Environmenta.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Devaraj SaravananD.Saravanan, currently working as Associate professor in the dept of operations&IT in IFHE University. His area of interest are image processing, data mining , Distributed computing.Video clustering is one of the.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Recently many applications have been created for categorizing, indexing and retrieving the digital video contents. These applications are used to handle a large quantity of video contents. Due to the restricted man-power, it is much required to develop retrieval methods that automatically extract features from videos and makes use of it. It is a good deal expected to build up the retrieval methods that use the features automatically extracted from videos. These features are nothing but the representation of physical contents such as motion, edge, color etc. The retrieval methods need information of how to integrate/use features for retrieving the exact videos according to the user query.This book further discusses about the basics of indexing, clustering and data mining in the video database.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Video clustering is one of the important task in video data mining. We discuss about the different video clustering techniques using hierarchical clustering algorithms like CURE, BIRCH, CHAMLEON. Set of video frames are clustered using the hierarchical clustering algorithms. As a result of comparison of results all the hierarchical algorithms offer good performance for some set of video files only. That is each clustering algorithm shows best clustering on particular video files only. It fails to forms best clusters of all type of video files. Hence we propose a hierarchical clustering algorithm that offers best clustering performance for all type of video files at any circumstancesVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Video clustering is one of the important task in video data mining. We discuss about the different video clustering techniques using hierarchical clustering algorithms like CURE, BIRCH, CHAMLEON. Set of video frames are clustered using the hierarchical clustering algorithms. As a result of comparison of results all the hierarchical algorithms offer good performance for some set of video files only. That is each clustering algorithm shows best clustering on particular video files only. It fails to forms best clusters of all type of video files. Hence we propose a hierarchical clustering algorithm that offers best clustering performance for all type of video files at any circumstances.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recently many applications have been created for categorizing, indexing and retrieving the digital video contents. These applications are used to handle a large quantity of video contents. Due to the restricted man-power, it is much required to develop retrieval methods that automatically extract features from videos and makes use of it. It is a good deal expected to build up the retrieval methods that use the features automatically extracted from videos. These features are nothing but the representation of physical contents such as motion, edge, color etc. The retrieval methods need information of how to integrate/use features for retrieving the exact videos according to the user query.This book further discusses about the basics of indexing, clustering and data mining in the video database.