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陈亚当 等: 基于差异化特征提取的交叉半监督语义分割网络 5869
[46] Rong WB, Li ZJ, Zhang W, Sun LN. An improved Canny edge detection algorithm. In: Proc. of the 2014 IEEE Int’l Conf. on
Mechatronics and Automation. Tianjin: IEEE, 2014. 577–582. [doi: 10.1109/ICMA.2014.6885761]
[47] Zhu XZ, Cheng DZ, Zhang Z, Lin S, Dai JF. An empirical study of spatial attention mechanisms in deep networks. In: Proc. of the 2019
IEEE/CVF Int’l Conf. on Computer Vision. Seoul: IEEE, 2019. 6687–6696. [doi: 10.1109/ICCV.2019.00679]
[48] Hariharan B, Arbeláez P, Bourdev L, Maji S, Malik J. Semantic contours from inverse detectors. In: Proc. of the 2011 Int’l Conf. on
Computer Vision. Barcelona: IEEE, 2011. 991–998. [doi: 10.1109/ICCV.2011.6126343]
[49] Zhang JR, Wu TY, Ding CH, Zhao HW, Guo GD. Region-level contrastive and consistency learning for semi-supervised semantic
segmentation. arXiv:2204.13314, 2022.
[50] Kimhi M, Kimhi S, Zheltonozhskii E, Litany O, Baskin C. Semi-supervised semantic segmentation via marginal contextual information.
Trans. on Machine Learning Research, 2024.
[51] Xiao H, Hong YT, Dong L, Yan DQ, Xiong JJ, Zhuang JY, Liang DT, Peng CB. Multi-level label correction by distilling proximate
patterns for semi-supervised semantic segmentation. IEEE Trans. on Multimedia, 2024, 26: 8077–8087. [doi: 10.1109/TMM.2024.
3374594]
[52] Ke ZH, Qiu D, Li KC, Yang Q, Lau RWH. Guided collaborative training for pixel-wise semi-supervised learning. In: Proc. of the 16th
European Conf. on Computer Vision (ECCV 2020). Glasgow: Springer, 2020. 429–445. [doi: 10.1007/978-3-030-58601-0_26]
[53] Guan DY, Huang JX, Xiao AR, Lu SJ. Unbiased subclass regularization for semi-supervised semantic segmentation. In: Proc. of the 2022
IEEE/CVF Conf. on Computer Vision and Pattern Recognition. New Orleans: IEEE, 2022. 9958–9968. [doi: 10.1109/CVPR52688.2022.
00973]
[54] Chen YD, Zhao YB, Wu EH. Robust semi-supervised video object segmentation with dynamic embedding. Journal of Beijing University
of Aeronautics and Astronautics, 2025, 51(7): 2253–2261 (in Chinese with English abstract). [doi: 10.13700/j.bh.1001-5965.2023.0354]
[55] You CY, Dai WC, Min YF, Staib L, Duncan JS. Bootstrapping semi-supervised medical image segmentation with anatomical-aware
contrastive distillation. In: Proc. of the 28th Int’l Conf. on Information Processing in Medical Imaging. San Carlos de Bariloche: Springer,
2023. 641–653. [doi: 10.1007/978-3-031-34048-2_49]
[56] Dai ZH, Liu HX, Le QV, Tan MX. CoAtNet: Marrying convolution and attention for all data sizes. In: Proc. of the 35th Int’l Conf. on
Neural Information Processing Systems. Virtual Event: Curran Associates Inc., 2021. 3965–3977.
[57] Xu Y, Shang L, Ye JX, Qian Q, Li YF, Sun BG, Li H, Jin R. Dash: Semi-supervised learning with dynamic thresholding. In: Proc. of the
38th Int’l Conf. on Machine Learning. 2021. 11525–11536.
[58] Zuo SM, Yu Y, Liang C, Jiang HM, Er S, Zhang C, Zhao T, Zha HY. Self-training with differentiable teacher. In: Proc. of the 2022
Findings of the Association for Computational Linguistics: NAACL 2022. Seattle: Association for Computational Linguistics, 2022.
933–949. [doi: 10.18653/v1/2022.findings-naacl.70]
[59] Bartolomei L, Teixeira L, Chli M. Perception-aware path planning for UAVs using semantic segmentation. In: Proc. of the 2020
IEEE/RSJ Int’l Conf. on Intelligent Robots and Systems (IROS). Las Vegas: IEEE, 2020. 5808–5815. [doi: 10.1109/IROS45743.2020.
9341347]
[60] Chen LC, Zhu YK, Papandreou G, Schroff F, Adam H. Encoder-decoder with atrous separable convolution for semantic image
segmentation. In: Proc. of the 15th European Conf. on Computer Vision. Munich: Springer, 2018. 833–851. [doi: 10.1007/978-3-030-
01234-2_49]
附中文参考文献:
[4] 田萱, 王亮, 丁琪. 基于深度学习的图像语义分割方法综述. 软件学报, 2019, 30(2): 440–468. http://www.jos.org.cn/1000-9825/5659.
htm [doi: 10.13328/j.cnki.jos.005659]
[8] 云飞, 殷雁君, 张文轩, 智敏. 融合注意力机制的对抗式半监督语义分割. 计算机工程与应用, 2023, 59(8): 254–262. [doi: 10.3778/
j.issn.1002-8331.2112-0484]
[9] 冯迅, 杨健, 周涛, 宫辰. 基于注意力机制及类别层次结构的弱监督目标定位. 软件学报, 2023, 34(10): 4916–4929. http://www.jos.org.
cn/1000-9825/6675.htm [doi: 10.13328/j.cnki.jos.006675]
[23] 许华杰, 肖毅烽. 基于多教师网络模型的半监督语义分割方法. 计算机科学, 2023, 50(12): 279–284. [doi: 10.11896/jsjkx.221000245]
[28] 刘腊梅, 宗佳旭, 肖振久, 兰海, 曲海成. 流形正则化的交叉一致性语义分割算法. 中国图象图形学报, 2022, 27(12): 3542–3552. [doi:
10.11834/jig.210571]
[29] 李一彤, 张长伦. 基于深度学习的半监督语义分割算法研究. 人工智能与机器人研究, 2023, 12(4): 328–339. [doi: 10.12677/AIRR.
2023.124036]

