7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
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...
In patch-based object recognition, using a compact visual codebook can boost computational efficiency and reduce memory cost. Nevertheless, compared with a large-sized codebook, it...
Statistical discrimination methods are suitable not only for classification but also for characterisation of differences between a reference group of patterns and the population u...
Carlos E. Thomaz, Nelson A. O. Aguiar, Sergio H. A...
Abstract. This paper proposes a novel face recognition method based on discriminant analysis with Gabor tensor representation. Although the Gabor face representation has achieved g...
Zhen Lei, Rufeng Chu, Ran He, ShengCai Liao, Stan ...