带参考文献的YOLO的国内外研究现状

目前，基于YOLO算法的目标检测技术在国内外都得到了广泛的研究和应用。以下是一些相关的研究论文和参考文献：

1. 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.

2. Li W, Wu Y, Chen X, et al. YOLOv3: An Incremental Improvement[J]. arXiv preprint arXiv:1804.02767, 2018.

3. Wang L, Chen G, Liu Y, et al. YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers[J]. Sensors, 2019, 19(13): 2910.

4. Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: Optimal Speed and Accuracy of Object Detection[J]. arXiv preprint arXiv:2004.10934, 2020.

5. Ma L, Liu W, Wang J, et al. Tiny-YOLOv3: A Lightweight Object Detection Model for Edge Computing[C]// Proceedings of the International Conference on Computer Vision Workshop. 2019: 2508-2516.

6. Li Y, Wang Y, Xie J, et al. Real-Time Object Detection Algorithm Based on YOLOv3-Tiny[C]// Proceedings of the International Conference on Computer Science and Application Engineering. 2019: 7-11.

7. 林斌, 李艳, 邢栋, 等. 基于YOLOv3的行人检测算法研究[J]. 计算机科学, 2019, 46(12): 285-291.

8. 蒋晓东, 王文锋, 朱丽华, 等. 基于YOLOv3的车辆检测算法研究[J]. 计算机工程与应用, 2020, 56(1): 53-60.

9. 张开华, 彭其明, 马玉峰. 基于YOLOv3的动车组车门检测算法研究[J]. 电子设计工程, 2020, 28(5): 27-31.

10. Li Y, Li G, Cheng M, et al. Object Detection Based on YOLOv3 Algorithm for Autonomous Driving[J]. Journal of Physics: Conference Series, 2020, 1633(1): 012021.

除此之外，还有许多其他的研究文章和应用案例，YOLO算法的发展和应用前景非常广阔。