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PolSF: PolSAR image dataset on San Francisco
Xu Liu, Licheng Jiao, Fang Liu
Polarimetric SAR data has the characteristics of all-weather, all-time and so on, which is widely used in many fields. However, the data of annotation is relatively small, which is…
Hierarchical Feature-Aware Tracking
Wenhua Zhang, Licheng Jiao, Jia Liu
In this paper, we propose a hierarchical feature-aware tracking framework for efficient visual tracking. Recent years, ensembled trackers which combine multiple component trackers…
A Survey of Deep Learning-based Object Detection
Licheng Jiao, Fan Zhang, Fang Liu +4
Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in peoples life, such as monitoring security, autonomous dr…
SAR Image Change Detection via Spatial Metric Learning with an Improved Mahalanobis Distance
Rongfang Wang, Jia-Wei Chen, Yule Wang +2
The log-ratio (LR) operator has been widely employed to generate the difference image for synthetic aperture radar (SAR) image change detection. However, the difference image gener…
Imbalanced Learning-based Automatic SAR Images Change Detection by Morphologically Supervised PCA-Net
Rongfang Wang, Jie Zhang, Jia-Wei Chen +2
Change detection is a quite challenging task due to the imbalance between unchanged and changed class. In addition, the traditional difference map generated by log-ratio is subject…
PolSAR Image Classification based on Polarimetric Scattering Coding and Sparse Support Matrix Machine
Xu Liu, Licheng Jiao, Dan Zhang +1
POLSAR image has an advantage over optical image because it can be acquired independently of cloud cover and solar illumination. PolSAR image classification is a hot and valuable t…