Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1959-1962, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1959-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1959-1962, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1959-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

INTELLIGENT DETECTION OF STRUCTURE FROM REMOTE SENSING IMAGES BASED ON DEEP LEARNING METHOD

L. Xin L. Xin
  • Shanghai Institute of Surveying and Mapping, Shanghai, China

Keywords: Remote Sensing Image, Land Use Monitoring, Deep Learning, Neural Network, Building

Abstract. Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.