9786200003645 - a discriminative model for age invariant face recognition di khan, musharraf hina; jondhale, kalpana (9 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. A Discriminative Model for Age Invariant Face Recognition | Musharraf Hina Khan (u. a.) | Taschenbuch | 68 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200003645 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[do…t]de | Anbieter: preigu.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The discriminative model is developed to address face matching in the presence of age variation. In this approach, each face is represented by designing a densely sampled local feature description scheme, in which Scale Invariant F…eature Transform (SIFT) and Multi-scale Local Binary Patterns (MLBP) serve as local descriptors. Since both SIFT-based local features and MLBP-based local features span a high- dimensional feature space, an algorithm called multi-feature discriminant analysis (MFDA) is used to process these two local feature spaces in a unified framework. The new proposed method is discriminative model with multi-scale robust local binary pattern (MRLBP). MLBP is not so robust to the noise present in the image. The proposed method uses MRLBP which serve as the local descriptor in the discriminative model to enhance the performance. 68 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khan Musharraf HinaKhan Musharraf Hina has received her ME (CSE) degree from M.G.M. s college of engineering. Her research interests are Image Processing, Pattern Recognition and Computer Vision.The di…scriminative model is develo.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The discriminative model is developed to address face matching in the presence of age variation. In this approach, each face is represented by designing a densely sampled local feature description scheme, in which Scale Invariant Featu…re Transform (SIFT) and Multi-scale Local Binary Patterns (MLBP) serve as local descriptors. Since both SIFT-based local features and MLBP-based local features span a high- dimensional feature space, an algorithm called multi-feature discriminant analysis (MFDA) is used to process these two local feature spaces in a unified framework. The new proposed method is discriminative model with multi-scale robust local binary pattern (MRLBP). MLBP is not so robust to the noise present in the image. The proposed method uses MRLBP which serve as the local descriptor in the discriminative model to enhance the performance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The discriminative model is developed to address face matching in the presence of age variation. In this approach, each face is represented by designing a densely sampled local feature description scheme, in which Scale Invariant Featur…e Transform (SIFT) and Multi-scale Local Binary Patterns (MLBP) serve as local descriptors. Since both SIFT-based local features and MLBP-based local features span a high- dimensional feature space, an algorithm called multi-feature discriminant analysis (MFDA) is used to process these two local feature spaces in a unified framework. The new proposed method is discriminative model with multi-scale robust local binary pattern (MRLBP). MLBP is not so robust to the noise present in the image. The proposed method uses MRLBP which serve as the local descriptor in the discriminative model to enhance the performance.
