Laser & Optoelectronics Progress, Volume. 56, Issue 22, 222801(2019)

Building Detection from Remote Sensing Images Based on Improved U-net

Xinlei Ren1、*, Yangping Wang1,2,4, Jingyu Yang1,3, and Decheng Gao4
Author Affiliations
  • 1School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 2Experiment Teaching Center on Computer Science, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 3Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China;
  • 4Gansu Provincial Key Laboratory of System Dynamics and Reliability of Rail Transport Equipment, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
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    References(24)

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    [11] Marmanis D, Wegner J D, Galliani S, Remote Sensing, Spatial Information Scienceset al. Semantic segmentation of aerial images with an ensemble of CNNs[J]. III-, 3, 473-480(2016).

    [14] Noh H, Hong S, Han B. Learning deconvolution network for semantic segmentation. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 1520-1528(2015).

    [15] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. ∥Navab N, Hornegger J, Wells W, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science. Cham: Springer, 9351, 234-241(2015).

    [17] Guillaume C, Cristian B A. 2019-04-07]. http:∥cs229.stanford.edu/proj2017/final-posters/5148174.pdf.(2017).

    [23] Mnih V. Machine learning for aerial image labeling[D]. Canada: University of Toronto, 64-73(2013).

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    Xinlei Ren, Yangping Wang, Jingyu Yang, Decheng Gao. Building Detection from Remote Sensing Images Based on Improved U-net[J]. Laser & Optoelectronics Progress, 2019, 56(22): 222801

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Apr. 8, 2019

    Accepted: May. 13, 2019

    Published Online: Nov. 2, 2019

    The Author Email: Ren Xinlei (121931236@qq.com)

    DOI:10.3788/LOP56.222801

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