Traffic classification is the ability to identify and categorize network traffic by application type. In this paper, we consider the problem of traffic classification in the netwo...
Jeffrey Erman, Anirban Mahanti, Martin F. Arlitt, ...
This paper proposes a statistic framework for segmenting textured areas over real images by discriminant snakes. Our active contour model has the ability to learn different textur...
Abstract. This paper presents a new Bayesian approach to hyperspectral image segmentation that boosts the performance of the discriminative classifiers. This is achieved by combin...
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...