Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics
文献类型:期刊论文
作者 | Ao-Xue Li; Ke-Xin Zhang; Li-Wei Wang |
刊名 | International Journal of Automation and Computing
![]() |
出版日期 | 2019 |
卷号 | 16期号:5页码:563-574 |
关键词 | Fine-grained image classification zero-shot learning deep feature learning domain adaptation semantic graph. |
ISSN号 | 1476-8186 |
DOI | 10.1007/s11633-019-1177-8 |
英文摘要 | Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task for two main reasons: lack of sufficient training data for every class and difficulty in learning discriminative features for representation. In this paper, to address the two issues, we propose a two-phase framework for recognizing images from unseen fine-grained classes, i.e., zero-shot fine-grained classification. In the first feature learning phase, we finetune deep convolutional neural networks using hierarchical semantic structure among fine-grained classes to extract discriminative deep visual features. Meanwhile, a domain adaptation structure is induced into deep convolutional neural networks to avoid domain shift from training data to test data. In the second label inference phase, a semantic directed graph is constructed over attributes of fine-grained classes. Based on this graph, we develop a label propagation algorithm to infer the labels of images in the unseen classes. Experimental results on two benchmark datasets demonstrate that our model outperforms the state-of-the-art zero-shot learning models. In addition, the features obtained by our feature learning model also yield significant gains when they are used by other zero-shot learning models, which shows the flexility of our model in zero-shot fine-grained classification. |
源URL | [http://ir.ia.ac.cn/handle/173211/42358] ![]() |
专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
作者单位 | The Key Laboratory of Machine Perception (MOE), School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China |
推荐引用方式 GB/T 7714 | Ao-Xue Li,Ke-Xin Zhang,Li-Wei Wang. Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics[J]. International Journal of Automation and Computing,2019,16(5):563-574. |
APA | Ao-Xue Li,Ke-Xin Zhang,&Li-Wei Wang.(2019).Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics.International Journal of Automation and Computing,16(5),563-574. |
MLA | Ao-Xue Li,et al."Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics".International Journal of Automation and Computing 16.5(2019):563-574. |
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。