In this paper, we propose a novel fine-grained dictionary learning method for image
classification. To learn a high-quality discriminative dictionary, three types of multispecific …

In this paper, we present a new approach of incorporating kernels into dictionary learning.
The kernel K-SVD algorithm (KKSVD), which has been introduced recently, shows an …

Dictionary learning (DL) has been successfully applied to various pattern classification tasks
in recent years. However, analysis dictionary learning (ADL), as a major branch of DL, has …

In this paper, we discuss the sparse codes auto-extractor based classification. A joint label
consistent embedding and dictionary learning approach is proposed for delivering a linear …

Multi-spectral face recognition has been attracting increasing interest. In the last decade,
several multi-spectral face recognition methods have been presented. However, it has not …

Functional MRI (fMRI) and diffusion MRI (dMRI) are non-invasive imaging modalities that
allow in-vivo analysis of a patient's brain network (known as a connectome). Use of these …

Recognizing facial images captured under visible light has long been discussed in the past
decades. However, there are many impact factors that hinder its successful application in …

Robust face recognition is an active topic in computer vision, while face occlusion is one of
the most challenging problems for robust face recognition algorithm. The latest research on …

A novel dictionary learning algorithm, namely reconstructive and discriminative dictionary
learning based on sparse representation classification criterion (RDDLSRCC), is proposed …

Sparse representation models based on dictionary learning have led to interesting results in
signal restoration and target recognition. However, due to the redundancy defined by …