1 |
https://nvidia.com
|
2 |
Liu Ting, Zhou Baijun, Zhao Yongsheng, and Yan Shun, Ship Detection Algorithm based on Improved YOLOv5, IEEE Xplore, 2022, Fab. 24, 2022.
|
3 |
https://public.roboflow.com/
|
4 |
https://github.com/ultralytics/YOLOv5.git
|
5 |
R. Girshick, "Fast R-CNN," IEEE Int. Conf. Comput. Vision, Santiago, Chile, Dec. 7-13, 2015, pp. 1440-1448.
|
6 |
Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, You Only Look Once: Unified, Real-Time Object Detection, arXiv:1506.02640v5 [cs.CV] 9 May 2016.
|
7 |
Xingkui Zhu1, Shuchang Lyu1, Xu Wang 1 Qi Zhao1, TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios, ICCV 2021 open access.
|
8 |
Ross. Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik, "Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation," IEEE Conf. Comput. Vision Pattern Recogn., Columbus, OH, USA, June 23-28, 2014, pp. 580-587.
|
9 |
J. Dai et al., "R-FCN: Object Detection via Region-based Fully Convolutional Networks," Conf. Neural Inform. Process. Syst., Barcelona, Spain, Dec. 4-6, 2016, pp. 379-387.
|
10 |
S. Ren et al., "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks," IEEE Trans. Pattern Anal. Mach. Intell., vol. 39, no. 6, 2017, pp. 1137-1149.
DOI
|
11 |
Pallavi Udatewar, et. el, Personal Protective Equipment Kit Detection using YOLOv5 and TensorFlow, IEEE Xplore, 2021, 2.
|
12 |
Qihai Cai, Shangping Zhong, Kaizhi Chen, Target Detection in Rural River Image Based on Yolo V5 Model with the Cross-Switch Unit, 2021 6th International Conference on Image, Vision and Computing (ICIVC) | 978-1-6654-4368-5/21/© 2021 IEEE | DOI: 10.1109/ICIVC52351.2021.9527005
DOI
|
13 |
W. Liu et al., "SSD: Single Shot MultiBox Detector," Eur. Conf. Comp. Vision, Amsterdam, Netherlands, Oct. 8- 16, 2016, pp. 21-37.
|
14 |
Tsung Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar, "Focal Loss for Dense Object Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 42, Issue 2, pp. 318-327, 2018.
DOI
|
15 |
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, and Qi Tian, "CenterNet: Keypoint Triplets for Object Detection", arXiv:1904.08189v3 [cs.CV] 19 Apr 2019.
|
16 |
Wei Ding, Li Zhang, Building Detection in Remote Sensing Image Based on Improved YOLOv5, IEEE Xplore, 2022, 2.
|
17 |
Guihui Shi, et. el, Combined Channel and Spatial Attention for YOLOv5 during Target Detection, IEEE Xplore, 2022, 2.
|
18 |
Guanhao Yang, et. el, Garbage Classification System with YOLOv5 Based on Image Recognition, IEEE Xplore, 2022, 2.
|
19 |
Tian-Hao Wu1, et. el, Real-Time Vehicle and Distance Detection Based on Improved YOLOv5 Network, IEEE Xplore, 2022, 2.
|
20 |
Zhiyue Zhang, et. el, Recognition of Casting Embossed Convex and Concave Characters Based on YOLOv5 for Different Distribution Conditions, IEEE, 2021, 2.
|
21 |
WenZe Fan, et. el, Research on Abnormal Target Detection Method in Chest Radiograph Based on YOLOv5 Algorithm, IEEE, 2021, 2.
|
22 |
Yaqi Guan, et. el, Design and Implementation of Safety Helmet Detection System Based on YOLOv5, 2021 2nd Asia Conference on Computers and Communications (ACCC)
|