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Image-Specific Classification With Local and Global Discriminations
Zhang, Chunjie1,2; Cheng, Jian2,3,4; Li, Changsheng5; Tian, Qi6
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
2018-09-01
Volume29Issue:9Pages:4479-4486
Corresponding AuthorZhang, Chunjie(chunjie.zhang@ia.ac.cn)
AbstractMost image classification methods try to learn classifiers for each class using training images alone. Due to the interclass and intraclass variations, it would be more effective to take the testing images into consideration for classifier learning. In this brief, we propose a novel image-specific classification method by combing the local and global discriminations of training images. We adaptively train classifier for each testing image instead of generating classifiers for each class with training images alone. For each testing image, we first select its k nearest neighbors in the training set with the corresponding labels for local classifier training. This helps to model the distinctive characters of each testing image. Besides, we also use all the training images for global discrimination modeling. The local and global discriminations are combined for final classification. In this way, we could not only model the specific character of each testing image but also avoid the local optimum by jointly considering all the training images. To evaluate the usefulness of the proposed image-specific classification with local and global discrimination (ISC-LG) method, we conduct image classification experiments on several public image data sets. The superior performances over other baseline methods prove the effectiveness of the proposed ISC-LG method.
KeywordGlobal information image-specific classification local information object categorization
DOI10.1109/TNNLS.2017.2748952
WOS KeywordOBJECT CATEGORIZATION ; NEURAL-NETWORKS ; LOW-RANK ; CLASSIFIERS ; MODEL
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61303154] ; National Natural Science Foundation of China[61332016] ; Scientific Research Key Program of Beijing Municipal Commission of Education[KZ201610005012] ; ARO[W911NF-15-1-0290] ; National Science Foundation of China[61429201] ; Faculty Research Gift Awards by the NEC Laboratories of America ; Faculty Research Gift Awards by the NEC Laboratories of Blippar ; National Natural Science Foundation of China[61303154] ; National Natural Science Foundation of China[61332016] ; Scientific Research Key Program of Beijing Municipal Commission of Education[KZ201610005012] ; ARO[W911NF-15-1-0290] ; National Science Foundation of China[61429201] ; Faculty Research Gift Awards by the NEC Laboratories of America ; Faculty Research Gift Awards by the NEC Laboratories of Blippar
Funding OrganizationNational Natural Science Foundation of China ; Scientific Research Key Program of Beijing Municipal Commission of Education ; ARO ; National Science Foundation of China ; Faculty Research Gift Awards by the NEC Laboratories of America ; Faculty Research Gift Awards by the NEC Laboratories of Blippar
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000443083700045
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15318
Collection类脑智能研究中心
Corresponding AuthorZhang, Chunjie
Affiliation1.Chinese Acad Sci, Inst Automat, Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 2728, Peoples R China
4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 2728, Peoples R China
5.Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 610051, Sichuan, Peoples R China
6.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Chunjie,Cheng, Jian,Li, Changsheng,et al. Image-Specific Classification With Local and Global Discriminations[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(9):4479-4486.
APA Zhang, Chunjie,Cheng, Jian,Li, Changsheng,&Tian, Qi.(2018).Image-Specific Classification With Local and Global Discriminations.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(9),4479-4486.
MLA Zhang, Chunjie,et al."Image-Specific Classification With Local and Global Discriminations".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.9(2018):4479-4486.
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