Joint Subspace and Dictionary Learning with Dynamic Training Set for Cross Domain Image Classification

2018 ◽  
pp. 502-517
Author(s):  
Yufeng Qiu ◽  
Songsong Wu ◽  
Kun Wang ◽  
Guangwei Gao ◽  
Xiaoyuan Jing
Keyword(s):  
Image Classification ◽  
Dictionary Learning ◽  
Training Set ◽  
Cross Domain

scholarly journals Semi-Supervised PolSAR Image Classification Based on Self-Training and Superpixels

2019 ◽  
Vol 11 (16) ◽  
pp. 1933 ◽  
Author(s):  
Yangyang Li ◽  
Ruoting Xing ◽  
Licheng Jiao ◽  
Yanqiao Chen ◽  
Yingte Chai ◽  
...  
Keyword(s):  
Image Classification ◽  
State Of The Art ◽  
Sample Selection ◽  
Spatial Relations ◽  
Speckle Noise ◽  
Classification Performance ◽  
Selection Strategy ◽  
Training Set ◽  
Polarimetric Synthetic Aperture Radar ◽  
Unlabeled Sample

Polarimetric synthetic aperture radar (PolSAR) image classification is a recent technology with great practical value in the field of remote sensing. However, due to the time-consuming and labor-intensive data collection, there are few labeled datasets available. Furthermore, most available state-of-the-art classification methods heavily suffer from the speckle noise. To solve these problems, in this paper, a novel semi-supervised algorithm based on self-training and superpixels is proposed. First, the Pauli-RGB image is over-segmented into superpixels to obtain a large number of homogeneous areas. Then, features that can mitigate the effects of the speckle noise are obtained using spatial weighting in the same superpixel. Next, the training set is expanded iteratively utilizing a semi-supervised unlabeled sample selection strategy that elaborately makes use of spatial relations provided by superpixels. In addition, a stacked sparse auto-encoder is self-trained using the expanded training set to obtain classification results. Experiments on two typical PolSAR datasets verified its capability of suppressing the speckle noise and showed excellent classification performance with limited labeled data.

A General Feature Paradigm for Unsupervised Cross-Domain PolSAR Image Classification

2021 ◽  
pp. 1-5
Author(s):  
Rong Gui ◽  
Xin Xu ◽  
Rui Yang ◽  
Zhaozhuo Xu ◽  
Lei Wang ◽  
...  
Keyword(s):  
Image Classification ◽  
General Feature ◽  
Cross Domain

Unsupervised Joint Subspace and Dictionary Learning for Enhanced Cross-Domain Person Re-Identification

2018 ◽  
Vol 12 (6) ◽  
pp. 1263-1275 ◽  
Author(s):  
Lei Qi ◽  
Jing Huo ◽  
Xiaocong Fan ◽  
Yinghuan Shi ◽  
Yang Gao
Keyword(s):  
Dictionary Learning ◽  
Cross Domain

scholarly journals Multi-View Analysis Dictionary Learning for Image Classification

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 20174-20183 ◽  
Author(s):  
Qianyu Wang ◽  
Yanqing Guo ◽  
Jiujun Wang ◽  
Xiangyang Luo ◽  
Xiangwei Kong
Keyword(s):  
Image Classification ◽  
Dictionary Learning

Transfer Dictionary Learning Method for Cross-Domain Multimode Process Monitoring and Fault Isolation

2020 ◽  
Vol 69 (11) ◽  
pp. 8713-8724 ◽  
Author(s):  
Keke Huang ◽  
Haofei Wen ◽  
Can Zhou ◽  
Chunhua Yang ◽  
Weihua Gui
Keyword(s):  
Process Monitoring ◽  
Dictionary Learning ◽  
Fault Isolation ◽  
Learning Method ◽  
Cross Domain
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