Chinese Journal of Liquid Crystals and Displays, Volume. 35, Issue 11, 1168(2020)
Real-time ship detection in satellite images based on YOLO-v3 model compression
[4] [4] REN S Q, HE K M, GIRSHICK R B, et al. Faster R-CNN: towards real-time object detection with region proposal networks [C]//Proceedings of Advances in Neural Information Processing Systems 28. Montreal, Quebec, Canada: NIPS, 2015: 91-99.
[5] [5] REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: unified, real-time object detection [C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE, 2016: 779-788.
[8] [8] REDMON J, FARHADI A. Yolov3: an incremental improvement [J]. arXiv: 1804.02767, 2018.
[9] [9] REDMON J, FARHADI A. YOLO9000: better, faster, stronger [C]//Proceedings of 2017 IEEE Computer Vision and Pattern Recognition. Honolulu, USA: IEEE, 2017: 6517-6525.
[10] [10] EVERINGHAM M, VAN GOOL L, WILLIAMS C K I, et al. The PASCAL visual object classes (VOC) challenge [J]. International Journal of Computer Vision, 2010, 88(2): 303-338.
[12] [12] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition [C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE, 2016: 770-778.
[13] [13] ZHANG P Y, ZHONG Y X, LI X Q. SlimYOLOv3: narrower, faster and better for real-time UAV applications [C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision Workshop. Seoul, Korea (South): IEEE, 2019: 37-45.
[14] [14] IOFFE S, SZEGEDY C. Batch normalization: accelerating deep network training by reducing internal covariate shift [C]//Proceedings of the 32nd International Conference on International Conference on Machine Learning. Lille, France: JMLR, 2015: 448-456.
[15] [15] LIU Z, LI J G, SHEN Z Q, et al. Learning efficient convolutional networks through network slimming [C]//Proceedings of 2017 IEEE International Conference on Computer Vision. Venice, Italy: IEEE, 2017: 2755-2763.
[16] [16] Airbus ship detection challenge [DB/OL]. https://www.kaggle.com/c/airbus-ship-detection.
[17] [17] SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition [C]//Proceedings of the 3rd International Conference on Learning Representations. San Diego, USA: ICLR, 2015: 1-14.
[18] [18] LIU W, ANGUELOV D, ERHAN D, et al. SSD: single shot multibox detector [C]//Proceedings of the 14th European Conference on Computer Vision. Amsterdam, The Netherlands: Springer, 2016: 21-37.
[19] [19] DAI J, LI Y, HE K, et al. R-FCN: object detection via region-based fully convolutional networks [C]//Proceedings of the 30th Conference on Neural Information Processing Systems. Barcelona, Spain: NIPS, 2016: 379-387.
Get Citation
Copy Citation Text
CHEN Ke-jun, ZHANG Ye. Real-time ship detection in satellite images based on YOLO-v3 model compression[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(11): 1168
Category:
Received: Mar. 25, 2020
Accepted: --
Published Online: Jan. 19, 2021
The Author Email: CHEN Ke-jun (ckj409399@sina.com)