[1] [1] 杨坚华， 张浩， 花海洋. 并行路径与强注意力机制遥感图像建筑物分割［J］. 光学 精密工程， 2023， 31（2）： 234-245. doi: 10.37188/ope.20233102.0234YANGJ H， ZHANGH， HUAH Y. Parallel path and strong attention mechanism for building segmentation in remote sensing images［J］. Opt. Precision Eng.， 2023， 31（2）： 234-245.（in Chinese）. doi: 10.37188/ope.20233102.0234

[2] [2] 贾建鑫， 孙海彬， 蒋长辉， 等. 多源遥感数据的道路提取技术研究现状及展望［J］. 光学 精密工程， 2021， 29（2）： 430-442. doi: 10.37188/OPE.20212902.0430JIAJ X， SUNH B， JIANGCH H， et al. Road extraction technology based on multi-source remote sensing：［J］. Opt. Precision Eng.， 2021， 29（2）： 430-442.（in Chinese）. doi: 10.37188/OPE.20212902.0430

[3] [3] 成丽波， 李昂臻， 贾小宁， 等. 小波多重分形遥感图像混合去噪［J］. 光学 精密工程， 2022， 30（15）： 1880-1888. doi: 10.37188/ope.20223015.1880CHENGL B， LIA ZH， JIAX N， et al. Removing mixed noise from remote sensing images by wavelet multifractal method［J］. Opt. Precision Eng.， 2022， 30（15）： 1880-1888.（in Chinese）. doi: 10.37188/ope.20223015.1880

[4] [4] 熊林. 无监督领域自适应目标检测方法研究［D］. 成都： 电子科技大学， 2022.XIONGL. Research on Unsupervised Adaptive Target Detection Method［D］. Chengdu： University of Electronic Science and Technology of China， 2022. （in Chinese）

[5] Z X LIU, L MA, Q DU. Class-wise distribution adaptation for unsupervised classification of hyperspectral remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 59, 508-521(2021).

[6] J J MIAO, B ZHANG, B WANG. Coarse-to-fine joint distribution alignment for cross-domain hyperspectral image classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 12415-12428(2021).

[7] Z Q FANG, Y X YANG, Z K LI et al. Confident learning-based domain adaptation for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-16(2022).

[8] X J LIANG, Y ZHANG, J P ZHANG. Attention multisource fusion-based deep few-shot learning for hyperspectral image classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 8773-8788(2021).

[9] N MAKKAR, L X YANG, S PRASAD. Adversarial learning based discriminative domain adaptation for geospatial image analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 150-162(2021).

[10] S BEN-DAVID, J BLITZER, K CRAMMER et al. Analysis of representations for domain adaptation, 137-144(2006).

[11] C VILLANI. Optimal Transport： Old and New(2009).

[12] G PEYRÉ, M CUTURI. Computational optimal transport： with applications to data science. Foundations and Trends® in Machine Learning, 11, 355-607(2019).

[13] K NGUYEN, D NGUYEN, T A VU-LE et al. Improving mini-batch optimal transport via partial transportation. arXiv, 2108-09645(2021). https：//arxiv.org/abs/2108.09645

[14] Y ZHANG, T LIU, M LONG et al. Bridging theory and algorithm for domain adaptation. arXiv, 1904-05801(2019). https：//arxiv.org/abs/1904.05801

[15] G LICCIARDI, F PACIFICI, D TUIA et al. Decision fusion for the classification of hyperspectral data： outcome of the 2008 GRS-S data fusion contest. IEEE Transactions on Geoscience and Remote Sensing, 47, 3857-3865(2009).

[16] 2018 IEEE GRSS Data Fusion Contest. Available：. http：//www. grss-ieee.org/community/technical-committees/data-fusion/

[17] T JOACHIMS. Transductive inference for text classification using support vector machines. Slovenia, 99, 200-209(1999).

[18] M S LONG, Y CAO, J M WANG et al. Learning transferable features with deep adaptation networks, 97-105(2015).

[19] Y GANIN, E USTINOVA, H AJAKAN et al. Domain-adversarial training of neural networks. Advances in Computer Vision and Pattern Recognition, 189-209(2017).

[20] B DENG, S JIA, D M SHI. Deep metric learning-based feature embedding for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 58, 1422-1435(2020).