Building topographic subspace model with transfer learning for sparse representation
文献类型：期刊论文
| 作者 | Liu, Yang1; Cheng, Jian1 ; Xu, Changsheng1,2; Lu, Hanqing1
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2010-06-01 |
| 卷号 | 73期号:10-12页码:1662-1668 |
| 关键词 | Transfer learning Topographic subspace model Sparse representation Image classification Image retrieval |
| 英文摘要 | In this paper, we propose a topographic subspace learning algorithm, named key-coding learning, which utilizes irrelevant unlabeled auxiliary data to facilitate image classification and retrieval tasks. It is worth noticing that we do not need to assume the auxiliary data follows the same class labels or generative distribution as the target training data. Firstly, the subspace model is learnt from enormous scale- and rotation-invariant SURF descriptors extracted from auxiliary and training images, which makes model insensitive to geometric and photometric image transformation. Then the bases of model are pooled by clustering to generate topographic basis banks. We provide insights to show that the topographic model is highly biologically plausible in simulating the complex cells in the visual cortex. Finally we generate the succinct sparse representations by mapping target data into this topographic model. Due to the capability of transferring knowledge, the proposed topographic subspace model can effectively address insufficient training data problem for image classification and is also helpful for generating discriminative features for image retrieval. Intensive experiments are conducted on three image datasets to evaluate the performance of our proposed model, the experimental results are encouraging and promising. (C) 2010 Elsevier B.V. All rights reserved. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | NATURAL IMAGES |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000279134100016 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3327]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China 2.China Singapore Inst Digital Media, Singapore, Singapore |
| 推荐引用方式 GB/T 7714 | Liu, Yang,Cheng, Jian,Xu, Changsheng,et al. Building topographic subspace model with transfer learning for sparse representation[J]. NEUROCOMPUTING,2010,73(10-12):1662-1668. |
| APA | Liu, Yang,Cheng, Jian,Xu, Changsheng,&Lu, Hanqing.(2010).Building topographic subspace model with transfer learning for sparse representation.NEUROCOMPUTING,73(10-12),1662-1668. |
| MLA | Liu, Yang,et al."Building topographic subspace model with transfer learning for sparse representation".NEUROCOMPUTING 73.10-12(2010):1662-1668. |
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。