Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (10): 57-64.DOI: 10.3778/j.issn.1002-8331.2101-0427

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Application of Deep Learning in High Resolution Remote Sensing Image Scene Classification

ZENG Li, XU Huiying, CHEN Xiaohao, QIAN Xiaoliang   

  1. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
  • Online:2021-05-15 Published:2021-05-10



  1. 郑州轻工业大学 电气信息工程学院,郑州 450002


Scene classification of high resolution remote sensing image is committed to automatically identify the types of land use or cover, which has important application value in military and land resources exploration. High resolution remote sensing image scene classification method based on deep learning has achieved better results than traditional methods, and it is also a hot spot of current research. This paper summarizes and comprehensively evaluates these methods. Firstly, according to the different ways of supervision, the popular methods based on deep learning are analyzed. Secondly, the popular methods under different supervision methods are evaluated quantitatively on three open data sets. Finally, the characteristics of different supervision methods are summarized, and the future development trend is prospected.

Key words: high resolution remote sensing image, deep learning, scene classification, supervision method



关键词: 高分遥感图像, 深度学习, 场景分类, 监督方式