A novel framework called 2D Fisher Discriminant Analysis
(2D-FDA) is proposed to deal with the Small Sample
Size (SSS) problem in conventional One-Dimensional Linear
Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
Nearest neighbor (NN) classification assumes locally constant class conditional probabilities, and suffers from bias in high dimensions with a small sample set. In this paper, we p...
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
This paper introduces a novel technique for palmprint recognition on the transform domain, based on combining principle component analysis (PCA) and Fourier domain. Principal Comp...
Moussadek Laadjel, Ahmed Bouridane, Fatih Kurugoll...
We consider the problem of publishing sensitive transaction data with privacy preservation. High dimensionality of transaction data poses unique challenges on data privacy and dat...
Yabo Xu, Benjamin C. M. Fung, Ke Wang, Ada Wai-Che...