Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …

The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

Visual attention has become a popular and widely used component for image recognition.
Although various attention-based methods have been proposed and achieved relatively …

Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse
coding is presented. In addition to using class labels of training data, we also associate label …

This paper presents a variational-based approach for fusing hyperspectral and multispectral
images. The fusion problem is formulated as an inverse problem whose solution is the target …

Hyperspectral image (HSI) anomaly detection (AD) generally considers background pixels
as low-rank distribution and anomaly pixels as sparse distribution. However, it is usually …

The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …

Sparse representation based classification has led to interesting image recognition results,
while the dictionary used for sparse coding plays a key role in it. This paper presents a novel …

Discriminative dictionary learning (DL) has been widely studied in various pattern
classification problems. Most of the existing DL methods aim to learn a synthesis dictionary …