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

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Xin, L.^1¹ 

[1] Shanghai Institute of Surveying and Mapping, Shanghai, China^1

关键词: Remote Sensing Image;    Land Use Monitoring;    Deep Learning;    Neural Network;    Building;   

DOI  :  10.5194/isprs-archives-XLII-3-1959-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

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.

【 授权许可】

CC BY