sparse representation-based classificationAs a powerful classifier, sparse representation-based classification (SRC) has successfully been applied in various visual recognition problems. However, due to the highly correlated bands and insufficient training samples of hyperspectral image (HSI) data, it still...
The proposed method is compared with six representative emotion classification methods, including linear discriminant classifier, K-nearest-neighbor, radial basis function neural networks, support vector machines, sparse representation-based classification and kernel sparse representation-based classification. ...
The proposed method was applied to global encoding on substitution matrix representation of protein sequences with the combination of weighted sparse representation classifier. In order to construct a sequence-based multiple classifier system for identifying PPIs, Xia et al. [14] adopted auto-...
Representation-based classification (SRC) is a face recognition breakthrough of recent years, but the dimensionality reduction for SRC has not been well addressed. The reason why existing dimensionality reduction methods are not effective for SRC is revealed for the first time. Based on analysis of...
SparseRepresentationClassifier(GMM-SRC)based classifier,anabsolutegainof1.27%and0.25%inEERcan beachievedrespectively. IndexTerms—sparserepresentation,compressive sensing,speakerverification 1.INTRODUCTION Anautomaticspeakerrecognitionsystemnormally comprisesthreestages:featureextraction,speaker modellingandscorecomputation....
In recent years, sparse representation-based classification (SRC) has made great progress in face recognition (FR). However, SRC emphasizes noise sparsity too much and it is not suitable for the real world. In this paper, we propose a robust l2,1-norm Sparse Representation framework that const...
Local feature-based methods gain importance in the recent years due to their robustness under degradation conditions. In this paper, a novel high-order local pattern descriptor in combination with sparse representation based classifier (SRC) is proposed for expression robust 3D face recognition. 3D ...
摘要: Sparse representation-based classification (SRC) and collaborative representation-based classification (CRC) have shown promising classification results. Both methods are distance-based classifiers, a关键词: Classifier fusion Collaborative representation Image classification Sparse representation ...
Since actual networks that are large also tend to be sparse20,21,22, obtaining a sparse representation of the network from high dimensional data becomes critical. In the context of neuronal networks, a primary reason for sparsity is the well-known fact23,24 that more than 50% of brain’s ...
Brain-computer interface (BCI) based on functional near-infrared spectroscopy (fNIRS) is expected to provide an optional active rehabilitation training method for patients with walking dysfunction, which will affect their quality of life seriously. Sparse representation classification (SRC) oxyhemoglobin (...