9783330048874 - biometric security system for watchlist surveillance von singh, anshul kumar (6 Ergebnisse)
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Taschenbuch. Zustand: Neu. Biometric Security System for Watchlist Surveillance | Anshul Kumar Singh | Taschenbuch | 60 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9783330048874 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter:…preigu.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Video-Surveillance is a wide area of research and various researchers doing research in this field from the last decade. In our approach, we used one of the reliable biometric of a human i.e. face. Here we are using well-known PCA (Pr…incipal Component Analysis) Algorithm for the training process of the system because it is one of the best dimensionality reduction and one of the reliable algorithms. The weakness of current algorithm is that, when this algorithm is used alone for a surveillance purpose it does not give best results and when it combines with some other techniques which provide good results with good speed and accuracy. Now a day most researchers are doing research with single image only. In our approach we are having only one image per person in a dataset, PCA alone does not work well with that single image. Our approach is to use PCA with NN (Nearest Neighbors) and having confidence value that is favorable to use with NN replacing threshold value concept of PCA. For a single image, we need to set a specific threshold value depending upon the environment for recognition. And it is itself a very challenging task. 60 pp. Englisch.
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh Anshul KumarEr. Anshul Kumar Singh is currently serving as Assistant Professor of Department of the Post Graduate Department of Computer Science & Engineering at Raja Balwan…t Singh Engineering Technical Campus, Bichpuri, Agra. .
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Video-Surveillance is a wide area of research and various researchers doing research in this field from the last decade. In our approach, we used one of the reliable biometric of a human i.e. face. Here we are using well-known PCA (Princi…pal Component Analysis) Algorithm for the training process of the system because it is one of the best dimensionality reduction and one of the reliable algorithms. The weakness of current algorithm is that, when this algorithm is used alone for a surveillance purpose it does not give best results and when it combines with some other techniques which provide good results with good speed and accuracy. Now a day most researchers are doing research with single image only. In our approach we are having only one image per person in a dataset, PCA alone does not work well with that single image. Our approach is to use PCA with NN (Nearest Neighbors) and having confidence value that is favorable to use with NN replacing threshold value concept of PCA. For a single image, we need to set a specific threshold value depending upon the environment for recognition. And it is itself a very challenging task.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Video-Surveillance is a wide area of research and various researchers doing research in this field from the last decade. In our approach, we used one of the reliable biometric of a human i.e. face. Here we are using well-known PCA (Princip…al Component Analysis) Algorithm for the training process of the system because it is one of the best dimensionality reduction and one of the reliable algorithms. The weakness of current algorithm is that, when this algorithm is used alone for a surveillance purpose it does not give best results and when it combines with some other techniques which provide good results with good speed and accuracy. Now a day most researchers are doing research with single image only. In our approach we are having only one image per person in a dataset, PCA alone does not work well with that single image. Our approach is to use PCA with NN (Nearest Neighbors) and having confidence value that is favorable to use with NN replacing threshold value concept of PCA. For a single image, we need to set a specific threshold value depending upon the environment for recognition. And it is itself a very challenging task.
