| Similarity learning for object recognition based on derived kernel | |
Li, Hong4; Wei, Yantao3; Li, Luoqing2; Yuan, Yuan1
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| 作者部门 | 光学影像分析与学习中心 |
| 2012-04-15 | |
| 发表期刊 | NEUROCOMPUTING
 |
| ISSN | 0925-2312 |
| 卷号 | 83页码:110-120 |
| 产权排序 | 4 |
| 摘要 | Recently, derived kernel method which is a hierarchical learning method and leads to an effective similarity measure has been proposed by Smale. It can be used in a variety of application domains such as object recognition, text categorization and classification of genomic data. The templates involved in the construction of the derived kernel play an important role. To learn more effective similarity measure, a new template selection method is proposed in this paper. In this method, the redundancy is reduced and the label information of the training images is used. In this way, the proposed method can obtain compact template sets with better discrimination ability. Experiments on four standard databases show that the derived kernel based on the proposed method achieves high accuracy with low computational complexity. |
| 文章类型 | Article |
| 关键词 | Derived Kernel Hierarchical Learning Image Similarity Neural Response Object Recognition Template Selection |
| 学科领域 | Computer Science |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1016/j.neucom.2011.12.005 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | FACE RECOGNITION ; IMAGE SIMILARITY ; CORTEX ; DECOMPOSITION ; DISTANCE ; FEATURES |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| WOS记录号 | WOS:000301613800013 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/20253 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China 2.Hubei Univ, Fac Math & Comp Sci, Wuhan 430062, Peoples R China 3.Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, Wuhan 430074, Peoples R China 4.Huazhong Univ Sci & Technol, Sch Math & Stat, Wuhan 430074, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Hong,Wei, Yantao,Li, Luoqing,et al. Similarity learning for object recognition based on derived kernel[J]. NEUROCOMPUTING,2012,83:110-120. |
| APA | Li, Hong,Wei, Yantao,Li, Luoqing,&Yuan, Yuan.(2012).Similarity learning for object recognition based on derived kernel.NEUROCOMPUTING,83,110-120. |
| MLA | Li, Hong,et al."Similarity learning for object recognition based on derived kernel".NEUROCOMPUTING 83(2012):110-120. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Similarity learning （1092KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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