Azimuth-Sensitive Object Detection in Sar Images Using Improved Yolo V5 Model-Reference-Cited by-同舟云学术

Azimuth-Sensitive Object Detection in Sar Images Using Improved Yolo V5 Model

Published:2022-07-17 Issue: Volume: Page:
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Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Ge Ji¹,Zhang Bo¹,Wang Chao¹,Xu Changgui¹,Tian Zhixin²,Xu Lu¹

Affiliation:

1. Aerospace Information Research Institute, Chinese Academy of Sciences,International Research Center of Big Data for Sustainable Development Goals,Beijing,China,100094

2. China Academy of Space Technology,Beijing,China,100094

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883072.pdf?arnumber=9883072

Reference12 articles.

1. YOLO9000: better, faster, stronger;redmon;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017

2. You only look once: Unified, real-time object detection;redmon;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2016

3. Searching for MobileNetV3

4. Yolov4: Optimal speed and accuracy of object detection;bochkovskiy;ArXiv Preprint,2020

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