UM
Sparse-based neural response for image classification
Hong Li1; Hongfeng Li1; Yantao Wei2; Yuanyan Tang3; Qiong Wang1
2014-11-20
Source PublicationNeurocomputing
ISSN0925-2312
Volume144Pages:198-207
Abstract

Image classification is a popular and challenging topic in the computer vision field. On the basis of advances in neuroscience, this paper proposes a sparse-based neural response feature extraction method for image classification. The approach extracts discriminative and invariant representations of images by alternating between non-negative sparse coding and maximum pooling operation with effectiveness. Additionally, effective template selection methods are proposed to further enhance the performance of the algorithm. In comparison with traditional hierarchical methods, our proposed model accounts for the neural processing of visual cortex in human brain, which appears to gain more beneficial discriminative and robust properties for image classification tasks. A variety of benchmarks are used to evaluate the algorithm. The experiment results demonstrate that our proposed algorithm achieves quite excellent or state-of-the-art performance compared with other popular methods. 

KeywordImage Classification Maximum Pooling Operation Neural Response Robust Sparse Coding
DOIhttps://doi.org/10.1016/j.neucom.2014.04.053
URLView the original
Indexed BySCIE
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000341677800019
PublisherELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
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Citation statistics
Cited Times [WOS]:8   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorHong Li; Hongfeng Li; Yantao Wei; Yuanyan Tang; Qiong Wang
Affiliation1.School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, China
2.Department of Information Technology, Central China Normal University, Wuhan 430079, China
3.Faculty of Science and Technology, University of Macau, Macau, China
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Hong Li,Hongfeng Li,Yantao Wei,et al. Sparse-based neural response for image classification[J]. Neurocomputing,2014,144:198-207.
APA Hong Li,Hongfeng Li,Yantao Wei,Yuanyan Tang,&Qiong Wang.(2014).Sparse-based neural response for image classification.Neurocomputing,144,198-207.
MLA Hong Li,et al."Sparse-based neural response for image classification".Neurocomputing 144(2014):198-207.
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