Classification problems are traditionally focused on uniclass samples, that is, each sample of the training and test sets has one unique label, which is the target of the classific...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
In general, digital images can be classified into photographs and computer graphics. This taxonomy is very useful in many applications, such as web image search. However, there ar...
Considering the statistical text classification problem we approximate class-conditional probability distributions by structurally modified Poisson mixtures. By introducing the st...
This work addresses the problem of in-the-dark traffic classification for TCP sessions, an important problem in network management. An innovative use of support vector machines (S...
William H. Turkett Jr., Andrew V. Karode, Errin W....