激光与光电子学进展, 2020, 57 (12): 121502, 网络出版: 2020-06-03   

基于改进YOLO v3的目标检测算法 下载: 2018次

Target Detection Algorithm Based on Improved YOLO v3
赵琼 1,2李宝清 1,*李唐薇 1,2
作者单位
1 中国科学院上海微系统与信息技术研究所微系统技术重点实验室, 上海 201800
2 中国科学院大学, 北京 100049
引用该论文

赵琼, 李宝清, 李唐薇. 基于改进YOLO v3的目标检测算法[J]. 激光与光电子学进展, 2020, 57(12): 121502.

Qiong Zhao, Baoqing Li, Tangwei Li. Target Detection Algorithm Based on Improved YOLO v3[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121502.

参考文献

[1] ViolaP, JonesM. Rapid object detection using a boosted cascade of simple features[C]∥Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, December 8-14, 2001, Kauai, HI, USA. New York: IEEE, 2001: 511- 518.

[2] 马娟娟, 潘泉, 梁彦, 等. 基于改进Grassberger熵随机森林分类器的目标检测[J]. 中国激光, 2019, 46(7): 0704011.

    Ma J J, Pan Q, Liang Y, et al. Object detection based on improved Grassberger entropy random forest classifier[J]. Chinese Journal of Lasers, 2019, 46(7): 0704011.

[3] GirshickR, DonahueJ, DarrellT, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 2014: 580- 587.

[4] Uijlings J R R, Gevers T, et al. Selective search for object recognition[J]. International Journal of Computer Vision, 2013, 104(2): 154-171.

[5] GirshickR. Fast R-CNN[C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2015: 1440- 1448.

[6] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149.

[7] 曹宇剑, 徐国明, 史国川. 基于旋转不变Faster R-CNN的低空装甲目标检测[J]. 激光与光电子学进展, 2018, 55(10): 101501.

    Cao Y J, Xu G M, Shi G C. Low altitude armored target detection based on rotation invariant Faster R-CNN[J]. Laser & Optoelectronics Progress, 2018, 55(10): 101501.

[8] DaiJ, LiY, HeK, et al. R-FCN: object detection via region-based fully convolutional networks[C]∥Conference and Workshop on Neural Information Processing Systems, December 5-10, 2016, Barcelona, Spain. New York: Curran Associates, 2016: 379- 387.

[9] Lin TY, DollarP, GirshickR, et al. Feature pyramid networks for object detection[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI. New York: IEEE, 2017: 2117- 2125.

[10] RedmonJ, DivvalaS, GirshickR, et al. You only look once: unified, real-time object detection[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 779- 788.

[11] RedmonJ, FarhadiA. YOLO9000: better, faster, stronger[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI. New York: IEEE, 2017: 7263- 7271.

[12] IoffeS, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift[EB/OL]. ( 2015-03-02)[2019-11-01]. https:∥arxiv.org/abs/1502. 03167.

[13] 魏湧明, 全吉成, 侯宇青阳. 基于YOLO v2的无人机航拍图像定位研究[J]. 激光与光电子学进展, 2017, 54(11): 111002.

    Wei Y M, Quan J C. Hou Y Q Y. Aerial image location of unmanned aerial vehicle based on YOLO v2[J]. Laser & Optoelectronics Progress, 2017, 54(11): 111002.

[14] LiuW, AnguelovD, ErhanD, et al. SSD: single shot MultiBox detector[M] ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 2016, 9905: 21- 37.

[15] FuC, LiuW, RangaA, et al. ( 2017-01-23)[2019-11-01]. https:∥ arxiv.org/abs/1701. 06659.

[16] 王俊强, 李建胜, 周学文, 等. 改进的SSD算法及其对遥感影像小目标检测性能的分析[J]. 光学学报, 2019, 39(6): 0628005.

    Wang J Q, Li J S, Zhou X W, et al. Improved SSD algorithm and its performance analysis of small target detection in remote sensing images[J]. Acta Optica Sinica, 2019, 39(6): 0628005.

[17] RedmonJ, Farhadi A. YOLOv3:an incremental improvement[EB/OL] ( 2018-04-08)[2019-11-01]. https:∥arxiv.org/abs/1804. 02767.

[18] Lin TY, GoyalP, GirshickR, et al. Focal loss for dense object detection[C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice. New York: IEEE, 2017: 2980- 2988.

[19] FanB, Niu JC, ZhaoJ. Three-phase full-controlled rectifier circuit fault diagnosis based on optimized neural networks[C]∥2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), August 8-10, 2011, Deng Feng, China. New York: IEEE, 2011: 6048- 6051.

赵琼, 李宝清, 李唐薇. 基于改进YOLO v3的目标检测算法[J]. 激光与光电子学进展, 2020, 57(12): 121502. Qiong Zhao, Baoqing Li, Tangwei Li. Target Detection Algorithm Based on Improved YOLO v3[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121502.

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