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CoLR: Classification-Oriented Local Representation for Image Recognition
Joint Authors
Guo, Tan
Zhang, Lei
Tan, Xiaoheng
Yang, Liu
Guo, Zhiwei
Wei, Fupeng
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-06-20
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Naïve sparse representation has stability problem due to its unsupervised nature, which is not preferred for classification tasks.
For this problem, this paper presents a novel representation learning method named classification-oriented local representation (CoLR) for image recognition.
The core idea of CoLR is to find the most relevant training classes and samples with test sample by taking the merits of class-wise sparseness weighting, sample locality, and label prior.
The proposed representation strategy can not only promote a classification-oriented representation, but also boost a locality adaptive representation within the selected training classes.
The CoLR model is efficiently solved by Augmented Lagrange Multiplier (ALM) scheme based on a variable splitting strategy.
Then, the performance of the proposed model is evaluated on benchmark face datasets and deep object features.
Specifically, the deep features of the object dataset are obtained by a well-trained convolutional neural network (CNN) with five convolutional layers and three fully connected layers on the challenging ImageNet.
Extensive experiments verify the superiority of CoLR in comparison with some state-of-the-art models.
American Psychological Association (APA)
Guo, Tan& Zhang, Lei& Tan, Xiaoheng& Yang, Liu& Guo, Zhiwei& Wei, Fupeng. 2019. CoLR: Classification-Oriented Local Representation for Image Recognition. Complexity،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132768
Modern Language Association (MLA)
Guo, Tan…[et al.]. CoLR: Classification-Oriented Local Representation for Image Recognition. Complexity No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1132768
American Medical Association (AMA)
Guo, Tan& Zhang, Lei& Tan, Xiaoheng& Yang, Liu& Guo, Zhiwei& Wei, Fupeng. CoLR: Classification-Oriented Local Representation for Image Recognition. Complexity. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132768
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132768