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- W2806866760 abstract "Several techniques have been proposed for face recognition that use global and local approaches for finding most eligible features for classification. Generally, methods based on localized feature selection techniques are found to be more robust towards illumination, pose and expression variations. In this paper, author has proposed an architecture that uses wavelet decomposition and informational entropy for finding localized discriminative coordinates in the image space for face recognition. The identified coordinates are supplied to a Gabor filters based face recognition model for classification. The proposed system uses single image per subject for training database and is able to achieve a recognition rate of 92.5% with ORL face database." @default.
- W2806866760 created "2018-06-13" @default.
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- W2806866760 date "2018-01-01" @default.
- W2806866760 modified "2023-09-27" @default.
- W2806866760 title "A Hybrid Feature Extraction Approach for Finding Local Discriminative Coordinates for Face Recognition" @default.
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- W2806866760 doi "https://doi.org/10.1007/978-981-10-8660-1_48" @default.
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