TITLE:
A Review of Researches on Deep Learning in Remote Sensing Application
AUTHORS:
Ming Zhu, Yongning He, Qingyu He
KEYWORDS:
Deep Learning, Remote Sensing Application, CNN, Land Cover Classification, Object Detection, Change Detection
JOURNAL NAME:
International Journal of Geosciences,
Vol.10 No.1,
January
10,
2019
ABSTRACT: In recent years, deep learning has been widely used in the field of image understanding and made breakthroughs research progress in image understanding. Because remote sensing application and image understanding are inseparable, researchers have carried out a lot of research on the
application of deep learning in remote sensing field, and extended the deep learning method to various application fields of remote sensing. This paper summarizes the basic principles of deep learning and its research progress and typical applications in remote sensing, introduces the current main deep learning model and its development history, focuses on the analysis and elaboration of the research status of deep learning in remote sensing image classification, object detection and change detection, and on this basis, summarizes the typical applications and their application effects. Finally, according to the current application of deep learning in remote sensing, the main problems and future development directions are summarized.