When facing extremely complex infrared background, due to the defect of l 1 norm based
sparsity measure, the state-of-the-art infrared patch-image (IPI) model would be in a …

Inverse problems are encountered in many domains of physics, with analytic continuation of
the imaginary Green's function into the real frequency domain being a particularly important …

Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial
role in the successful treatment of the disease and the effective reduction of deaths. In this …

Images are susceptible to various kinds of noises, which corrupt the pictorial information
stored in the images. Image de-noising has become an integral part of the image processing …

Wasserstein discriminant analysis (WDA) is a new supervised linear dimensionality
reduction algorithm. Following the blueprint of classical Fisher Discriminant Analysis, WDA …

Abstract Model building and parameter estimation are traditional concepts widely used in
chemical, biological, metallurgical, and manufacturing industries. Early modeling …

In the present paper, we propose a new approach for realistic image noise modeling based
on a generative adversarial network (GAN). The model aims to boost performance of a deep …

This paper proposes a unified vision-based manipulation framework using image contours
of deformable/rigid objects. Instead of explicitly defining the features by geometries or …

Benefiting from the recent real image dataset, learning-based approaches have achieved
good performance for real-image denoising. To further improve the performance for Bayer …

It is important in image restoration to remove noise while preserving meaningful details such
as blurred thin edges and low-contrast fine features. The existing edge-preserving …