98 citations · 209 across the 17 of their papers we have counts for
14 papers · 1 filter
TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning
Chao Tao, Ji Qia, Guo Zhang +3
Do we on the right way for remote sensing image understanding (RSIU) by training models via supervised data-dependent and task-dependent way, instead of human vision in a label-fre…
Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images
Qing Zhu, Shengzhi Huang, Han Hu +3
Detecting the changes of buildings in urban environments is essential. Existing methods that use only nadir images suffer from severe problems of ambiguous features and occlusions…
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection
Yinjie Lei, Duo Peng, Pingping Zhang +2
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging ta…
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples
Chao Tao, Ji Qi, Weipeng Lu +2
With the development of deep learning, supervised learning methods perform well in remote sensing images (RSIs) scene classification. However, supervised learning requires a huge n…
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification
Haifeng Li, Zhenqi Cui, Zhiqing Zhu +4
Training a modern deep neural network on massive labeled samples is the main paradigm in solving the scene classification problem for remote sensing, but learning from only a few d…
DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images
Jie Chen, Ziyang Yuan, Jian Peng +5
Change detection is a basic task of remote sensing image processing. The research objective is to identity the change information of interest and filter out the irrelevant change i…