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https://github.com/ggsDing/Bi-SRNet


https://github.com/ggsDing/Bi-SRNet

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# Bi-SRNet
Pytorch codes of 'Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images' [[paper]](https://ieeexplore.ieee.org/document/9721305)




**Data preparation:**
1. Split the SCD data into training, validation and testing (if available) set and organize them as follows:

>YOUR_DATA_DIR
> - Train
> - im1
> - im2
> - label1
> - label2
> - Val
> - im1
> - im2
> - label1
> - label2
> - Test
> - im1
> - im2
> - label1
> - label2

2. Find *-datasets -RS_ST.py*, set the data root in *Line 22* as *YOUR_DATA_DIR*

**Reference**

If you find our work useful or interesting, please consider to cite:
> Ding L, Guo H, Liu S, et al. Bi-temporal semantic reasoning for the semantic change detection in hr remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022.