Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …

The learning of image representation is always the most important problem in computer
vision community. In this paper, we propose a novel image representation method by …

Joint decision-making is one of the coordination mechanisms to address the inherent
complexity of business-to-business (B2B) processes within a supply chain. Joint decision …

Microarray gene expression data gained great importance in recent years due to its role in
disease diagnoses and prognoses which help to choose the appropriate treatment plan for …

In this paper different model-based methods of classification of global patterns in
dermoscopic images are proposed. Global patterns identification is included in the pattern …

In this paper, we propose a multi-kernel classifier learning algorithm to optimize a given
nonlinear and nonsmoonth multivariate classifier performance measure. Moreover, to solve …

Human action recognition is a hot research topic; however, the change in shapes, the high
variability of appearances, dynamitic background, potential occlusions in different actions …

A method for automatic image annotation based on multi-feature fusion and multi-label
learning algorithm was proposed in this paper. In the process of feature fusion, rotation …

In this paper, a novel pattern classification approach is proposed by regularizing the
classifier learning to maximize mutual information between the classification response and …

In this paper, we propose a supervised distance metric learning method for the problem of
matching people in different but non-overlapping camera pictures, which is an important and …