May 2, 2016 · This paper reports a study that propose a semi-supervised method called DSLM, which aims at overcoming all these limitations. The proposed ...
The proposed method ensures that the discriminative information of labeled data and the intrinsic geometric structure of data are mapped to new optimal subspace ...
Two of the most popular techniques for this purpose are Principal Component. Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is an unsupervised and ...
The proposed method ensures that the discriminative information of labeled data and the intrinsic geometric structure of data are mapped to new optimal subspace ...
1 Face recognition based on LDA in manifold subspaceHung Phuoc Truong1, Tue-Minh Dinh Vo1 and Thai Hoang Le1, *1Faculty of Information Technology ...
The proposed method ensures that the discriminative information of labeled data and the intrinsic geometric structure of data are mapped to new optimal subspace ...
Face recognition using LDA-based algorithms - ResearchGate
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Oct 22, 2024 · In this paper, we propose a new algorithm that deals with both of the shortcomings in an efficient and cost effective manner.
Subspace methods for face recognition - ScienceDirect.com
www.sciencedirect.com › article › abs › pii
The objective of this paper is to provide a comprehensive performance evaluation of about twenty five different subspace algorithms under several important ...
Jun 10, 2008 · In this correspondence, we describe a holistic face recognition method based on subspace Linear Discriminant Analysis (LDA).
Missing: manifold | Show results with:manifold
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Fisher Linear Discriminant Analysis (LDA) has been successfully used as a data discriminantion technique for face recognition. This paper has developed a ...