Discriminative graph regularized broad learning system for image recognition
文献类型:期刊论文
作者 | Jin, Junwei1; Liu, Zhulin1; Chen, C. L. Philip1,2,3 |
刊名 | SCIENCE CHINA-INFORMATION SCIENCES
![]() |
出版日期 | 2018-11-01 |
卷号 | 61期号:11页码:14 |
关键词 | broad learning system deep learning graph regularization image recognition feature extraction incremental learning |
ISSN号 | 1674-733X |
DOI | 10.1007/s11432-017-9421-3 |
通讯作者 | Chen, C. L. Philip(philip.chen@ieee.org) |
英文摘要 | Broad learning system (BLS) has been proposed as an alternative method of deep learning. The architecture of BLS is that the input is randomly mapped into series of feature spaces which form the feature nodes, and the output of the feature nodes are expanded broadly to form the enhancement nodes, and then the output weights of the network can be determined analytically. The most advantage of BLS is that it can be learned incrementally without a retraining process when there comes new input data or neural nodes. It has been proven that BLS can overcome the inadequacies caused by training a large number of parameters in gradient-based deep learning algorithms. In this paper, a novel variant graph regularized broad learning system (GBLS) is proposed. Taking account of the locally invariant property of data, which means the similar images may share similar properties, the manifold learning is incorporated into the objective function of the standard BLS. In GBLS, the output weights are constrained to learn more discriminative information, and the classification ability can be further enhanced. Several experiments are carried out to verify that our proposed GBLS model can outperform the standard BLS. What is more, the GBLS also performs better compared with other state-of-the-art image recognition methods in several image databases. |
WOS关键词 | MULTILAYER FEEDFORWARD NETWORKS ; RESTRICTED BOLTZMANN MACHINE ; ROBUST FACE RECOGNITION ; TIME-SERIES PREDICTION ; FUNCTIONAL-LINK NET ; FUNCTION APPROXIMATION ; NEURAL-NETWORKS ; REPRESENTATION ; CLASSIFICATION |
资助项目 | National Natural Science Foundation of China[61572540] ; Macau Science and Technology Development Fund (FDCT)[019/2015/A] ; Macau Science and Technology Development Fund (FDCT)[024/2015/AMJ] ; Macau Science and Technology Development Fund (FDCT)[079/2017/A2] ; University Macau MYR Grants |
WOS研究方向 | Computer Science ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000447851800001 |
出版者 | SCIENCE PRESS |
资助机构 | National Natural Science Foundation of China ; Macau Science and Technology Development Fund (FDCT) ; University Macau MYR Grants |
源URL | [http://ir.ia.ac.cn/handle/173211/28127] ![]() |
专题 | 离退休人员 |
通讯作者 | Chen, C. L. Philip |
作者单位 | 1.Univ Macau, Fac Sci & Technol, Macau 999078, Peoples R China 2.Dalian Maritime Univ, Dalian 116026, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China |
推荐引用方式 GB/T 7714 | Jin, Junwei,Liu, Zhulin,Chen, C. L. Philip. Discriminative graph regularized broad learning system for image recognition[J]. SCIENCE CHINA-INFORMATION SCIENCES,2018,61(11):14. |
APA | Jin, Junwei,Liu, Zhulin,&Chen, C. L. Philip.(2018).Discriminative graph regularized broad learning system for image recognition.SCIENCE CHINA-INFORMATION SCIENCES,61(11),14. |
MLA | Jin, Junwei,et al."Discriminative graph regularized broad learning system for image recognition".SCIENCE CHINA-INFORMATION SCIENCES 61.11(2018):14. |
入库方式: OAI收割
来源:自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。