Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1265-1270

Metric learning based on intrinsic structural characteristics of data

Zhang Kaifanga
Lang Guilina
Wang Xiaominga,b
Huang Zengxia
Du Yajuna
a. School of Computer & Software Engineering, b. Robotics Research Center, Xihua University, Chengdu 610039, China
DOI: 10.19734/j.issn.1001-3695.2020.03.0054

Abstract

PCML as a typical metric learning method, which combines with SVM, exhibits superior performance in image recog-nition and person re-identification. However, in the process of learning the metric matrix, this method simply considers the margin between samples of different categories, ignoring that the feature space of samples of the same category also changes. To this end, this paper proposed a metric learning method based on the intrinsic structural characteristics of data. First of all, compared with PCML, the method not only considered the margin between samples of different categories, but also considered the intra-class divergence matrix of samples of the same category, so that the learned metric matrix had stronger discrimination ability. Secondly, it further transformed the l1-norm loss function into the l2-norm loss function, which could further improve the generalization performance of the model. Finally, the experimental results on multiple datasets show that the proposed method achieves better performance than other methods in most cases.

Foundation Support

国家自然科学基金项目(61602390)
西华大学研究生创新基金项目(ycjj2019085)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.03.0054
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Technology of Graphic & Image
Pages: 1265-1270
Serial Number: 1001-3695(2021)04-059-1265-06

Publish History

[2021-04-05] Printed Article

Cite This Article

张开放, 郎贵林, 王晓明, 等. 基于数据内在结构特征的度量学习 [J]. 计算机应用研究, 2021, 38 (4): 1265-1270. (Zhang Kaifang, Lang Guilin, Wang Xiaoming, et al. Metric learning based on intrinsic structural characteristics of data [J]. Application Research of Computers, 2021, 38 (4): 1265-1270. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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