In the digital multimedia era, digital forensics is becoming an emerging area of research
thanks to the large amount of image and video files generated. Ensuring the integrity of such …

UNet and its variations achieve state-of-the-art performances in medical image
segmentation. In end-to-end learning, the training with high-resolution medical images …

This paper describes the combined detection of coating and rust damages on painted metal
structures through the multiclass image segmentation technique. Our prior works were …

Percentage mammographic breast density (MBD) is one of the most notable biomarkers. It is
assessed visually with the support of radiologists with the four qualitative Breast Imaging …

In this paper, we propose a Dirichlet process (DP) mixture model of Gamma distributions,
which is an extension of the finite Gamma mixture model to the infinite case. In particular, we …

The accurate detection of abnormalities in medical images (like X-ray and CT scans) is a
challenging problem due to images' blurred boundary contours, different sizes, variable …

In this paper, we propose a novel hybrid discriminative learning approach based on shifted-
scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address …

In order to improve the information retrieval and resource sharing abilities of the library and
establish an intelligent library information management system, alibrary management …

For a better detection in Network information security monitoring system, the author
proposes a method based on adaptive depth detection. A deep belief network (DBN) was …

In long-term visual tracking, target occlusion and out-of-view are common problems that lead
to target loss. Adding a re-detection module to the short-term tracking algorithm is a general …