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[IEEE TGRS 2024] [RAGRNet] Recurrent Adaptive Graph Reasoning Network with Region and Boundary Interaction for Salient Object Detection in Optical Remote Sensing Images.

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RAGRNet

This project provides the code and results for 'Recurrent Adaptive Graph Reasoning Network with Region and Boundary Interaction for Salient Object Detection in Optical Remote Sensing Images', IEEE TGRS, 2024 (IEEE Link).

Network Architecture

RAGRNet.png

Datasets

The datasets utilized in this work can be accessed from BaiDuYunlink (code:2r9f), including ORSSD, EORSSD, and ORSI-4199.

Salmaps

The salmaps can be accessed from BaiDuYunlink (code:RAGR), including ORSSD, EORSSD, and ORSI-4199.

Evaluation Tool

You can use the evaluation tool (MATLAB version) to evaluate the above saliency maps.

Table.png

New 🚩

We provide saliency maps in BaiDuYunlink(code:RAGR) for UGSet Dataset.

Citation

If you find this work interesting and use our dataset in your research, please cite:

@article{zhao2024recurrent,
  title={Recurrent Adaptive Graph Reasoning Network with Region and Boundary Interaction for Salient Object Detection in Optical Remote Sensing Images},
  author={Zhao, Jie and Jia, Yun and Ma, Lin and Yu, Lidan},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2024},
  publisher={IEEE}
}

If you encounter any problems with the code, want to report bugs, etc.

Please contact me at [email protected].

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[IEEE TGRS 2024] [RAGRNet] Recurrent Adaptive Graph Reasoning Network with Region and Boundary Interaction for Salient Object Detection in Optical Remote Sensing Images.

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