Medical image fusion is important in image-guided medical diagnostics, treatment, and other
computer vision tasks. However, most current approaches assume that the source images …

Hyperspectral image (HSI) classification, which aims to assign an accurate label for
hyperspectral pixels, has drawn great interest in recent years. Although low-rank …

This paper addresses the problem of face recognition when there is only few, or even only a
single, labeled examples of the face that we wish to recognize. Moreover, these examples …

Industrial Internet-of-Things (IIoT) has revolutionized almost every aspect of industrial
manufacturing through industrial intelligence by incorporating production equipment, mobile …

Despite the fact that different objects possess distinct class-specific features, they also
usually share common patterns. This observation has been exploited partially in a recently …

Among various physiological signal acquisition methods for the study of the human brain,
EEG (Electroencephalography) is more effective. EEG provides a convenient, non-intrusive …

Both interclass variances and intraclass similarities are crucial for improving the
classification performance of discriminative dictionary learning (DDL) algorithms. However …

In this paper, we aim at learning robust and discriminative subspaces from noisy data.
Subspace learning is widely used in extracting discriminative features for classification …

Recently, a multi-view dictionary learning (DL) technique has received much attention.
Although some multi-view DL methods have been presented, they suffer from the problem of …

Subspace clustering is an effective technique for segmenting data drawn from multiple
subspaces. However, for time series data (eg, human motion), exploiting temporal …