Soufiane Ezghari

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We propose in this paper, a gender recognition solution under the presence of occlusion and using the very restrict samples in the learning base. The developed approach is based on the extraction of pertinent 3D depth-radial curves that cover the nose region and combined dimensionality reduction using sparse random projection method; furthermore we propose(More)
In this paper, we propose a fuzzy similarity based classification approach for 3D face recognition. In the feature extraction method, we exploit curve concept to represent the 3D facial data, two types of curves was considered: depth-level and depth-radial curves. As the dimension of the obtained features is high, the problem “curse of(More)
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