Konu "Face Recognition" için Fakülteler listeleme
Toplam kayıt 8, listelenen: 1-8
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A comparison of the Common Vector and the discriminative Common Vector methods for face recognition
(2005)The Common Vector (CV) method is a successful method which has been originally proposed for isolated word recognition problems in the case where the number of samples for each class is less than or equal to the dimensionality ... -
A fast method for the implementation of common vector approach
(Elsevier Science Inc, 2010)In this paper a novel computation method is proposed to perform the common vector approach (CVA) faster than its conventional implementation in pattern recognition. While conventional CVA calculations perform the classification ... -
Modular Common Vector Approach
(IEEE, 2014)The performance of a face recognition system is negatively affected by the accessories used on the face Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not at ... -
Modular common vector approach [Modüler ortak vektör yaklaşimi]
(IEEE Computer Society, 2014)The performance of a face recognition system is negatively affected by the accessories used on the face. Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not ... -
A new implementation of common matrix approach using third-order tensors for face recognition
(Pergamon-Elsevier Science LTD, 2011)In the classical common matrix approach (CMA), the common matrix for each individual face class is obtained using basis matrices calculated by Gram-Schmidt orthogonalization of the class covariance matrix. This common ... -
A new solution to one sample problem in face recognition using FLDA
(Elsevier Science Inc, 2011)Fisher linear discriminant analysis (FLDA) is a very popular method in face recognition. But FLDA fails when one image per person is available. This is due to the fact that the within-class scatter matrices cannot be ... -
Patch warping based face frontalization [Yama çarpitma tabanli yüz önleştirme]
(Institute of Electrical and Electronics Engineers Inc., 2018)Face frontalization increases accuracies of face and gesture recognition applications. In this paper, we propose a 2D patch warping based face frontalization method which that has a simple but efficient flow due to its ... -
Two-dimensional subspace classifiers for face recognition
(Elsevier Science BV, 2009)The subspace classifiers are pattern classification methods where linear subspaces are used to represent classes. In order to use the classical subspace classifiers for face recognition tasks, two-dimensional (2D) image ...