In this paper, we propose volume based local Gabor binary patterns (V-LGBP) for face representation and recognition. In our method, the Gabor feature set of each gray image is reg...
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
Traditional linear Fukunaga-Koontz Transform (FKT) [1] is a powerful discriminative subspaces building approach. Previous work has successfully extended FKT to be able to deal wit...
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
Feiping Nie, Shiming Xiang, Yangqiu Song, Changshu...
—This paper studies the problem of understanding noisy and structurally deformed two-dimensional images by means of abstractly defined neural works. First, in the framework of sy...