| Image-Specific Classification With Local and Global Discriminations | |
Zhang, Chunjie1,2 ; Cheng, Jian2,3,4; Li, Changsheng5; Tian, Qi6
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| Source Publication | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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| ISSN | 2162-237X |
| 2018-09-01 | |
| Volume | 29Issue:9Pages:4479-4486 |
| Corresponding Author | Zhang, Chunjie(chunjie.zhang@ia.ac.cn) |
| Abstract | Most 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. |
| Keyword | Global information image-specific classification local information object categorization |
| DOI | 10.1109/TNNLS.2017.2748952 |
| WOS Keyword | OBJECT CATEGORIZATION ; NEURAL-NETWORKS ; LOW-RANK ; CLASSIFIERS ; MODEL |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 ; 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 Organization | National 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 Area | Computer Science ; Engineering |
| WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| WOS ID | WOS:000443083700045 |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/15318 |
| Collection | 类脑智能研究中心 |
| Corresponding Author | Zhang, Chunjie |
| Affiliation | 1.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 Affilication | Institute of Automation, Chinese Academy of Sciences |
| Corresponding Author Affilication | Institute 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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| FINAL VERSION.pdf（571KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
| tnnls Image-Specific（151KB） | 开放获取 | -- | View Download | |||
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