.png){kind=icon}
返回
Domain adaptive collaborative representation based classification
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-018-7007-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Conventional representation based classification methods, such as sparse representation based classification (SRC) and collaborative representation based classification (CRC) have been developed and shown great potential due to its effectiveness in various recognition tasks. However, when the test data and training data come from different distribution, the performance of SRC and CRC will be degraded significantly. Recently, several sparse representation based domain adaptation learning (DAL) methods have been proposed and achieve impressive performance. However, these sparse representation based DAL methods need to solve the l(1)-norm optimization problem, which is extremely time-consuming. To address this problem, in this paper, we propose a simple yet much more efficient domain adaptive collaborative representation-based classification method (DACRC). By replacing the l(2)-norm regularization term using the l(2)-norm, we exploit the collaborative representation rather than sparse representation to jointly learn projections of data in the two domains. In addition, a common dictionary is also learned such that in the projected space the learned dictionary can optimal represent both training and test data. Furthermore, the proposed method is effective to deal with multiple domains problem and is easy to kernelized. Compared with other sparse representation based DAL methods, DACRC is computationally efficient and its performance is better or comparable to many state-of-the-art methods.
Keyword:
Domain adaptation
Collaborative representation
Joint projection and dictionary learning
Non-linear representation
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
机构
暂无机构信息
引用论文
Visuomotor perimetry in fish: A new approach to the functional analysis of altered visual pathways鱼的视觉运动视野检查: 一种对改变的视觉通路进行功能分析的新方法
PREAI
分享收藏Label propagation based on collaborative representation for face recognition.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
查看更多内容