Affiliation:
1. Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Abstract
Target detection in optical remote sensing images using deep-learning technologies has a wide range of applications in urban building detection, road extraction, crop monitoring, and forest fire monitoring, which provides strong support for environmental monitoring, urban planning, and agricultural management. This paper reviews the research progress of the YOLO series, SSD series, candidate region series, and Transformer algorithm. It summarizes the object detection algorithms based on standard improvement methods such as supervision, attention mechanism, and multi-scale. The performance of different algorithms is also compared and analyzed with the common remote sensing image data sets. Finally, future research challenges, improvement directions, and issues of concern are prospected, which provides valuable ideas for subsequent related research.
Funder
Natural Science Foundation Key Project of Gansu Province
Natural Science Foundation of Gansu Province
key talent project of Gansu Province
Key R & D and achievement transformation project of Inner Mongolia Autonomous Region
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Cited by
6 articles.
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