C2-YOLO: Rotating Object Detection Network for Remote Sensing Images with Complex Backgrounds
Author:
Affiliation:
1. School of Computer Science and Technology, University of Science and Technology,Nanjing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9891857/9889787/09891999.pdf?arnumber=9891999
Reference37 articles.
1. R2cnn: rotational region cnn for orientation robust scene text detection;jiang;ArXiv Preprint,2017
2. R3det: Refined single-stage detector with feature refinement for rotating object[J];yang;ArXiv Preprint,2019
3. Axis Learning for Orientated Objects Detection in Aerial Images
4. Learning RoI Transformer for Oriented Object Detection in Aerial Images
5. RBA-CenterNet: Feature Enhancement by Rotated Border Alignment for Oriented Object Detection
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2. Oriented Object Detection in Aerial Images Based on the Scaled Smooth L1 Loss Function;Remote Sensing;2023-02-28
3. Training YOLO v4 on DOTA dataset;2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI);2023-01-19
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