Recent research emphasizes more on analyzing multiple features to improve face
recognition (FR) performance. One popular scheme is to extend the sparse representation …

In this paper, we address the problem of robust face recognition using undersampled data.
Given only one or few face images per class, our proposed method not only handles test …

This paper analyzes the role of dictionary selection in Sparse Representation-based
Classification (SRC). While SRC introduces interesting results in the field of classification, its …

The efficacy and efficiency of SIFT have made it a state-of-art feature descriptor. It has been
widely used in many computer vision applications such as image classification. A large …

Recently support vector machines (SVM) using spatial pyramid matching (SPM) kernel have
been highly successful in image classification applications. And linear spatial pyramid …

This paper proposes a novel Bayesian method for the dictionary learning (DL) based
classification using Beta-Bernoulli process. We utilize this non-parametric Bayesian …

In this paper, we propose an automated method to classify normal/abnormal wall motion in
Left Ventricle (LV) function in cardiac cine-Magnetic Resonance Imaging (MRI). Without the …

提出了一种用于视觉分类任务的低计算复杂度且有效的图像表示方法. 把协作表示和判别信息
结合在统一框架内, 是基于协作表示分类方法的一种扩展形式. 测试样本的协作表示系数是稀疏 …

We present a multi-attributed dictionary learning algorithm for sparse coding. Considering
training samples with multiple attributes, a new distance matrix is proposed by jointly …

Growing evidence from the functional neuroimaging field suggests that human brain
functions are realized via dynamic functional interactions on large-scale structural networks …