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- Title
A Review: Remote Sensing Image Object Detection Algorithm Based on Deep Learning.
- Authors
Bai, Chenshuai; Bai, Xiaofeng; Wu, Kaijun
- 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.
- Subjects
DEEP learning; OBJECT recognition (Computer vision); REMOTE sensing; OPTICAL remote sensing; ALGORITHMS; FOREST monitoring; URBAN planning
- Publication
Electronics (2079-9292), 2023, Vol 12, Issue 24, p4902
- ISSN
2079-9292
- Publication type
Article
- DOI
10.3390/electronics12244902