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Titlebook: Audio- and Video-Based Biometric Person Authentication; Third International Josef Bigun,Fabrizio Smeraldi Conference proceedings 2001 Spri

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11#
發(fā)表于 2025-3-23 09:42:24 | 只看該作者
Galaxies and How to Observe Themor feature vector based upon the Gabor wavelet transformation of face images and using different orientation and scale local features. Independent Component Analysis (ICA) operates then on the Gabor feature vector subject to sensitivity analysis for the ICA transformation. Finally, the IGF method ap
12#
發(fā)表于 2025-3-23 16:25:13 | 只看該作者
Galaxies, Cluster of Galaxies & their dataigned to be robust against changes of facial expressions and viewpoints and are described by Gabor Wavelet filter in the 2D domain and Point Signature in the 3D domain. Localizing feature points in a new image is based on 3D-2D correspondence, their relative position and corresponding Bunch (coverin
13#
發(fā)表于 2025-3-23 19:35:54 | 只看該作者
Galaxies, Cluster of Galaxies & their data hair styles, and so on. This paper proposes a method of face recognition by using support vector machines with the feature set extracted by genetic algorithms. By selecting the feature set that has superior performance in recognizing faces, the use of unnecessary information of the faces can be avo
14#
發(fā)表于 2025-3-24 00:02:08 | 只看該作者
15#
發(fā)表于 2025-3-24 03:34:52 | 只看該作者
Accessories and Optical Quantitiesences between women and men in human face recognition. The women had higher correct answer frequencies then men in all face recognition questions they answered. In difficult questions, those which had fewer correct answers than other questions, the performance of the best skilled women were remarkab
16#
發(fā)表于 2025-3-24 07:53:44 | 只看該作者
https://doi.org/10.1007/978-1-84628-699-5o capture the substantial facial features and reduce computational complexity, we propose to use wavelet transform (WT) to decompose face images and choose the lowest resolution subband coefficients for face representation. Results indicate that our scheme yields accurate recognition on the widely u
17#
發(fā)表于 2025-3-24 14:05:02 | 只看該作者
Catalogs, Data, and Nomenclatureave demonstrated high generalization capabilities in many different tasks, including the object recognition problem. ICA is a feature extraction technique which can be considered a generalization of Principal Component Analysis (PCA). ICA has been mainly used on the problem of blind signal separatio
18#
發(fā)表于 2025-3-24 17:28:52 | 只看該作者
19#
發(fā)表于 2025-3-24 22:08:41 | 只看該作者
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發(fā)表于 2025-3-24 23:25:09 | 只看該作者
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