This paper explores the scope of spatial domain sparse representation for the application to
develop a fast and robust remote end face recognition (FR) scheme in the framework of …

Radiomics is a rapidly growing field in which sophisticated imaging features are extracted
from radiology images to predict clinical outcomes/responses, genetic alterations, and other …

We present a probabilistic modeling and inference framework for discriminative analysis
dictionary learning under a weak supervision setting. Dictionary learning approaches have …

The sparse representation based classification methods has achieved significant
performance in recent years. To fully exploit both the holistic and locality information of face …

In recent years, sparse coding via dictionary learning has been widely used in many
applications for exploiting sparsity patterns of data. For classification, useful sparsity patterns …

Recognizing human actions across different views is challenging, since observations of the
same action often vary greatly with viewpoints. To solve this problem, most existing methods …

Machine hearing or listening represents an emerging area. Conventional approaches rely
on the design of handcrafted features specialized to a specific audio task and that can hardly …

Classifier training plays an important role in image classification, while a good classifier
could more effectively exploit the discriminative information of input features to separate the …

In this paper, we formulate the soccer video event detection task as a sparse representation
problem by learning a supervised, discriminative and event-oriented dictionary based on …

为克服人脸表情图像识别过程中光照, 遮挡等带来的影响, 减少稀疏表示分类的时间,
提出一种融合HOG 特征和改进KC-FDDL (K-means Cluster and Fisher Discrimination …