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Remote Sensing Image Object Detection Method Based On Improved YOLOv3 Cover

Remote Sensing Image Object Detection Method Based On Improved YOLOv3

By: Zhiyuan Lu and  Bailin Liu  
Open Access
|May 2023

References

  1. Zou Z, Shi Z, Guo Y, et al. Object detection in 20 years: A survey[J]. arXiv preprint arXiv:1905.05055, 2019.
  2. Dalal N, Triggs B. Histograms of oriented gradients for human detection[C]//2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05). Ieee, 2005, 1: 886–893.
  3. Felzenszwalb P, McAllester D, Ramanan D. A discriminatively trained, multiscale, deformable part model[C]//2008 IEEE conference on computer vision and pattern recognition. Ieee, 2008: 1–8.
  4. Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2014: 580–587.
  5. Girshick R. Fast r-cnn[C]//Proceedings of the IEEE international conference on computer vision. 2015: 1440–1448.
  6. Ren S, He K, Girshick R, et al. Faster r-cnn: Towards real-time object detection with region proposal networks[J]. Advances in neural information processing systems, 2015, 28.
  7. Redmon J, Divvala S, Girshick R, et al. You only look once: Unified, real-time object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779–788.
  8. Redmon J, Farhadi A. YOLO9000: better, faster, stronger[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 7263–7271.
  9. Redmon J, Farhadi A. Yolov3: An incremental improvement[J]. arXiv preprint arXiv:1804.02767, 2018.
  10. Liu W, Anguelov D, Erhan D, et al. Ssd: Single shot multibox detector[C]//European conference on computer vision. Springer, Cham, 2016: 21–37.
  11. Lin T Y, Goyal P, Girshick R, et al. Focal loss for dense object detection[C]//Proceedings of the IEEE international conference on computer vision. 2017: 2980–2988.
  12. Tuia D, Persello C, Bruzzone L. Domain adaptation for the classification of remote sensing data: An overview of recent advances[J]. IEEE geoscience and remote sensing magazine, 2016, 4(2): 41–57.
  13. Li K, Wan G, Cheng G, et al. Object detection in optical remote sensing images: A survey and a new benchmark[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 159: 296–307.
  14. Liu S, Qi L, Qin H, et al. Path aggregation network for instance segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 8759–8768.
  15. Ge Z, Liu S, Li Z, et al. Ota: Optimal transport assignment for object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021: 303–312.
  16. Lin T Y, Dollár P, Girshick R, et al. Feature pyramid networks for object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 2117–2125.
Language: English
Page range: 1 - 8
Published on: May 26, 2023
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Zhiyuan Lu, Bailin Liu, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.