Fuzzy weighted sparse reconstruction error-steered semi-supervised learning for face recognition

Liu Li; Chen Siqi; Chen Xiuxiu; Wang Tianshi; Zhang Long

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Fuzzy weighted sparse reconstruction error-steered semi-supervised learning for face recognition

机译：模糊加权稀疏重建误区面部识别的半监督学习

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摘要

Since the number of labeled data is limited in the semi-supervised learning settings, we propose a fuzzy weighted sparse reconstruction error-steered semi-supervised learning method for face recognition. The fuzzy membership functions are introduced to the reconstruction error calculation for the unlabeled data. A weight function is utilized to capture the locality property of data when learning the sparse coefficients. The fuzzy weighted sparse reconstruction error-steered semi-supervised learning not only inherits the advantages of sparse representation classification techniques and neighborhood methods, but also steers the reconstruction errors of unlabeled data. Experimental studies on well-known face image datasets demonstrate that the proposed method outperforms the comparative approaches.

机译：由于标记数据的数量在半监督学习设置中受到限制，因此我们提出了一种模糊加权稀疏重建误差引导的面部识别半监督学习方法。模糊隶属函数被引入未标记数据的重建误差计算。在学习稀疏系数时，利用权重函数来捕获数据的位置特性。模糊加权稀疏重建错误 - 引导的半监督学习不仅继承了稀疏表示分类技术和邻域方法的优势，还使重建数据的重建误差引导。众所周知的面部图像数据集的实验研究表明，所提出的方法优于比较方法。

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来源
《The Visual Computer》 |2020年第8期|1521-1534|共14页
作者
Liu Li; Chen Siqi; Chen Xiuxiu; Wang Tianshi; Zhang Long;
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作者单位

Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China;

Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China;

Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China;

Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China;

Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Shandong Peoples R China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Membership function; Sparse representation; Fuzzy;

机译：会员功能;稀疏表示;模糊;

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1. Semi-Supervised Learning via Geodesic Weighted Sparse Representation [J] . Jianqiao WANG, Yuehua LI, Jianfei CHEN, IEICE transactions on information and systems . 2014,第6期

机译：测地加权稀疏表示的半监督学习
2. Semi-Supervised Learning via Geodesic Weighted Sparse Representation [J] . Jianqiao WANG, Yuehua LI, Jianfei CHEN, IEICE transactions on information and systems . 2014,第6期

机译：测地加权稀疏表示的半监督学习
3. Graph Construction Based on Re-weighted Sparse Representation for Semi-supervised Learning [J] . Yikai Wang, Yueqi Zhao, Longtong Zhang, Journal of information and computational science . 2013,第2期

机译：基于重加权稀疏表示的半监督学习图构造
4. A Semi-supervised Learning Algorithm Based on Low Rank and Weighted Sparse Graph for Face Recognition [C] . Tao Zhang, Zhenmin Tang, Bin Qian Chinese Conference on biometric recognition . 2016

机译：基于低秩和加权稀疏图的半监督人脸识别算法
5. Learning in semi-supervised model and sparse model. [D] . Xu, Jin. 2012

机译：在半监督模型和稀疏模型中学习。
6. A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine [O] . Qing Ye, Hao Pan, Changhua Liu 2015

机译：基于模糊熵和稀疏贝叶斯极限学习机的终传动同时故障诊断框架
7. Semi-Supervised Boosting Using Similarity Learning Based on Modular Sparse Representation With Marginal Representation Learning of Graph Structure Self-Adaptive [O] . Shu Hua Xu, Fei Gao 2020

机译：基于模块化稀疏表示与边缘表示学习的模块化稀疏表示，使用相似性学习的半监督增强

Fuzzy weighted sparse reconstruction error-steered semi-supervised learning for face recognition

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