[1] Liu X X, Chen Y P, Wei M Q et al. Building instance extraction method based on improved hybrid task cascade[J]. IEEE Geoscience and Remote Sensing Letters, 19, 3002005(2021).

[2] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[C], 3431-3440(2015).

[3] Badrinarayanan V, Kendall A, Cipolla R. SegNet: a deep convolutional encoder-decoder architecture for image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 2481-2495(2017).

[4] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. Medical image computing and computer-assisted intervention-MICCAI 2015, 9351, 234-241(2015).

[5] Chen L C, Papandreou G, Schroff F et al. Rethinking atrous convolution for semantic image segmentation[EB/OL]. https://arxiv.org/abs/1706.05587v3

[6] Liu W T, Li S H, Qin Y C. Automatic building roof extraction with fully convolutional neural network[J]. Journal of Geo-Information Science, 20, 1562-1570(2018).

[7] Qiu W Y, Gu L J, Gao F et al. Building extraction from very high-resolution remote sensing images using refine-UNet[J]. IEEE Geoscience and Remote Sensing Letters, 20, 6002905(2023).

[8] He Z M, Ding H Y, An B Q. E-Unet: a atrous convolution-based neural network for building extraction from high-resolution remote sensing images[J]. Acta Geodaetica et Cartographica Sinica, 51, 457-467(2022).

[9] Jin S, Guan M, Bian Y C et al. Building extraction from remote sensing images based on improved U-Net[J]. Laser & Optoelectronics Progress, 60, 0401002(2023).

[10] Liu J B, Huang H G, Sun H X et al. LRAD-net: an improved lightweight network for building extraction from remote sensing images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 675-687(2022).

[11] Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C], 7132-7141(2018).

[12] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

[13] Hu M H, Li J T, Yao Y J et al. SER-UNet algorithm for building extraction from high-resolution remote sensing image combined with multipath[J]. Acta Geodaetica et Cartographica Sinica, 52, 808-817(2023).

[14] Wang H Y, Miao F. Building extraction from remote sensing images using deep residual U-Net[J]. European Journal of Remote Sensing, 55, 71-85(2022).

[15] Lü S Y, Li J T, A X H et al. Res＿ASPP＿UNet++: building an extraction network from remote sensing imagery combining depthwise separable convolution with atrous spatial pyramid pooling[J]. National Remote Sensing Bulletin, 27, 502-519(2023).

[16] Zhang Z X, Liu Q J, Wang Y H. Road extraction by deep residual U-Net[J]. IEEE Geoscience and Remote Sensing Letters, 15, 749-753(2018).

[17] Ding X H, Guo Y C, Ding G G et al. ACNet: strengthening the kernel skeletons for powerful CNN via asymmetric convolution blocks[C], 1911-1920(2019).

[18] Li R, Duan C X, Zheng S Y et al. MACU-net for semantic segmentation of fine-resolution remotely sensed images[J]. IEEE Geoscience and Remote Sensing Letters, 19, 8007205(2022).

[19] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Computer vision-ECCV 2018, 11211, 3-19(2018).

[20] Liu Y C, Shao Z R, Hoffmann N. Global attention mechanism: retain information to enhance channel-spatial interactions[EB/OL]. https://arxiv.org/abs/2112.05561v1

[21] Yang M K, Yu K, Zhang C et al. DenseASPP for semantic segmentation in street scenes[C], 3684-3692(2018).

[22] Ji S P, Wei S Q, Lu M. Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 574-586(2019).

[23] Mnih V. Machine learning for aerial image labeling[D](2013).

[24] Sun K, Zhao Y, Jiang B R et al. High-resolution representations for labeling pixels and regions[EB/OL]. https://arxiv.org/abs/1904.04514

[25] Li R, Zheng S Y, Duan C X et al. Land cover classification from remote sensing images based on multi-scale fully convolutional network[J]. Geo-spatial Information Science, 25, 278-294(2022).

[26] Wang L B, Fang S H, Meng X L et al. Building extraction with vision transformer[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 5625711(2022).

[27] Wang L B, Li R, Duan C X et al. A novel transformer based semantic segmentation scheme for fine-resolution remote sensing images[J]. IEEE Geoscience and Remote Sensing Letters, 19, 6506105(2022).

[28] Zhang R H, Zhang Q, Zhang G X. SDSC-UNet: dual skip connection ViT-based U-shaped model for building extraction[J]. IEEE Geoscience and Remote Sensing Letters, 20, 6005005(2023).