@ARTICLE{10976421,
  author={Lyu, Shuchang and Zhao, Qi and Sun, Yaxuan and Cheng, Guangliang and He, Yiwei and Wang, Guangbiao and Ren, Jinchang and Shi, Zhenwei},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={Unsupervised Domain Adaptation for VHR Urban Scene Segmentation via Prompted Foundation Model-Based Hybrid Training Joint-Optimized Network}, 
  year={2025},
  volume={63},
  number={},
  pages={1-17},
  keywords={Remote sensing;Training;Decoding;Semantic segmentation;Foundation models;Adversarial machine learning;Adaptation models;Semantics;Feature extraction;Optimization;Hybrid training;prompted foundation model;semantic segmentation;unsupervised domain adaptation (UDA);urban scene;very-high-resolution (VHR) images},
  doi={10.1109/TGRS.2025.3564216}}