development performance evaluation texture von naik jatothu (5 Ergebnisse)

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Taschenbuch. Zustand: Neu. Development and Performance Evaluation of Texture Based CBIR Algorithm | Image Retrieval Methods | Jatothu Brahmaiah Naik (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204200828 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book proposes a content-based image retrieval (CBIR) system that employs an informative pattern-based descriptor. Recent literature has reported the development of efficient local-pattern-based descriptors, including the local vector pattern (LVP). This article extends the LVP formulation by making it more computationally efficient and informative. In the extended LVP-based extraction process, the global index angles are determined using the mutual information between the patterns, which are obtained from a pair of indexed angles. 180 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book proposes a content-based image retrieval (CBIR) system that employs an informative pattern-based descriptor. Recent literature has reported the development of efficient local-pattern-based descriptors, including the local vector pattern (LVP). This article extends the LVP formulation by making it more computationally efficient and informative. In the extended LVP-based extraction process, the global index angles are determined using the mutual information between the patterns, which are obtained from a pair of indexed angles.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book proposes a content-based image retrieval (CBIR) system that employs an informative pattern-based descriptor. Recent literature has reported the development of efficient local-pattern-based descriptors, including the local vector pattern (LVP). This article extends the LVP formulation by making it more computationally efficient and informative. In the extended LVP-based extraction process, the global index angles are determined using the mutual information between the patterns, which are obtained from a pair of indexed angles.