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Multi-granularity semantic alignment distillation learning for remote sensing image semantic segmentation

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References

  1. Cheng G, Xie X, Han J, Guo L, Xia G S. Remote sensing image scene classification meets deep learning: challenges, methods, benchmarks, and opportunities. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 3735–3756

    Article  Google Scholar 

  2. Li C, Mao Y, Zhang R, Huai J. A revisit to MacKay algorithm and its application to deep network compression. Frontiers of Computer Science, 2020, 14(4): 144304

    Article  Google Scholar 

  3. Hinton G, Vinyals O, Dean J. Distilling the knowledge in a neural network. 2015, arXiv preprint arXiv: 1503.02531

  4. Liu Y, Chen K, Liu C, Qin Z, Luo Z, Wang J. Structured knowledge distillation for semantic segmentation. In: Proceedings of 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019, 2599–2608

  5. Wang Y, Zhou W, Jiang T, Bai X, Xu Y. Intra-class feature variation distillation for semantic segmentation. In: Proceedings of the 16th European Conference on Computer Vision. 2020, 346–362

  6. Hou Y, Ma Z, Liu C, Loy C C. Learning lightweight lane detection CNNs by Self Attention distillation. In: Proceedings of 2019 IEEE/CVF International Conference on Computer Vision. 2019, 1013–1021

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Acknowledgements

This work was supported by the Special Funds for Innovation of Graduate Students Double Top University Plan in China University of Mining and Technology (No. 2018ZZCX14).

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Authors and Affiliations

  1. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China

    Di Zhang, Yong Zhou, Jiaqi Zhao & Rui Yao

  2. Engineering Research Center of Mine Digitization, Ministry of Education of the People’s Republic of China, Xuzhou, 221116, China

    Di Zhang, Yong Zhou, Jiaqi Zhao, Zhongyuan Yang, Hui Dong & Rui Yao

  3. College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China

    Huifang Ma

Authors
  1. Di Zhang
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  2. Yong Zhou
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  3. Jiaqi Zhao
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  4. Zhongyuan Yang
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  5. Hui Dong
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  6. Rui Yao
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  7. Huifang Ma
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Corresponding author

Correspondence to Yong Zhou.

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Supporting information The supporting information is available online at https://journal.hep.cn and https://link.springer.com.

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Zhang, D., Zhou, Y., Zhao, J. et al. Multi-granularity semantic alignment distillation learning for remote sensing image semantic segmentation. Front. Comput. Sci. 16, 164351 (2022). https://doi.org/10.1007/s11704-022-1505-y

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  • DOI: https://doi.org/10.1007/s11704-022-1505-y

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