Affiliated with RCfalse
A novel fusion strategy for probabilistic sparse representation classifier guided by support vector machines
Zhou,Jianhang; Zeng,Shaoning; Zhang,Bob
Source PublicationProceedings of SPIE - The International Society for Optical Engineering
Conference DateMAY 10-13, 2019
Conference PlaceSun Yat Sen Univ, Guangzhou, PEOPLES R CHINA

In recent object recognition research, the Sparse Representation based Classifier (SRC) and Collaborative Representation based Classification (CRC) have been widely used, achieving promising performances and robustness. However, both of these two algorithms are seldomly fused in classification based on the theory of probability. In this paper, we propose a novel image classification algorithm named Probabilistic Sparse-Collaborative Representation based Classifier (PSCRC), by fusing SRC and CRC. To boost the recognition performance and maintain the robustness of SRC, we introduce the theory of probability to offer different weights for each element in the coefficient vectors of SRC and CRC, respectively. We generate the probabilities of each sample in the training set by using Support Vector Machines (SVMs) which are fused with the coefficients of SRC and CRC. The proposed method is verified on five popular real word image datasets while being compared with other classifiers. The numerical results in the experiments show that the proposed classifier using our fusion strategy outperforms others.

KeywordClassifier Fusion Collaborative Representation Object Recognition Sparse Representation
URLView the original
Indexed ByCPCI-S
WOS Research AreaOptics
WOS SubjectOptics
WOS IDWOS:000511106700112
Scopus ID2-s2.0-85072620124
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Corresponding AuthorZhang,Bob
AffiliationPAMI Research Group,Department of Computer and Information Science,University of Macau,Taipa,Macao
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhou,Jianhang,Zeng,Shaoning,Zhang,Bob. A novel fusion strategy for probabilistic sparse representation classifier guided by support vector machines[C],2019.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhou,Jianhang]'s Articles
[Zeng,Shaoning]'s Articles
[Zhang,Bob]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhou,Jianhang]'s Articles
[Zeng,Shaoning]'s Articles
[Zhang,Bob]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhou,Jianhang]'s Articles
[Zeng,Shaoning]'s Articles
[Zhang,Bob]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.