1 |
边星, 晋良海, 陈雁高, 等. 施工作业人员佩戴安全帽行为意向研究. 中国安全科学学报, 2016, 26 (11): 43- 48.
|
2 |
李海元. 浅析工程建设项目投资管理与决策. 商讯, 2020, (18): 154- 155.
|
3 |
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.
|
4 |
GIRSHICK R. Fast R-CNN [C]//Proceedings of the IEEE International Conference on Computer Vision. 2015: 1440-1448.
|
5 |
REN S, HE K, GIRSHICK R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks [C]//Advances in Neural Information Processing Systems. 2015: 91-99.
|
6 |
REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: Unified, real-time object detection [C]//IEEE Conference on Computer Vision and Pattern Recognition. 2016: 779-788.
|
7 |
LIU W, ANGUELOV D, ERHAN D, et al. SSD: Single shot multibox detector [C]//European Conference on Computer Visio. 2016: 21-37.
|
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 |
LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2020, 42 (2): 318- 327.
|
10 |
REDMON J, FARHADI A. YOLOv3: An incremental improvement [EB/OL]. (2018-04-08)[2021-06-12]. https://arxiv.org/abs/1804.02767.
|
11 |
BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: Optimal speed and accuracy of object detection [EB/OL]. (2020-04-23)[2021-06-12]. https://arxiv.org/abs/2004.10934.
|
12 |
施辉, 陈先桥, 杨英. 改进YOLOv3的安全帽佩戴检测方法. 计算机工程与应用, 2019, 55 (11): 213- 220.
|
13 |
方明, 孙腾腾, 邵桢. 基于改进YOLOv2的快速安全帽佩戴情况检测. 光学精密工程, 2019, 27 (5): 1196- 1205.
|
14 |
乌民雨, 陈晓辉. 一种基于改进YOLOv3的安全帽检测方法. 信息通信, 2020, (6): 12- 14.
|
15 |
徐守坤, 王雅如, 顾玉宛, 等. 基于改进区域卷积神经网络的安全帽佩戴检测. 计算机工程与设计, 2020, 41 (5): 1385- 1389.
|
16 |
SANDLER M, HOWARD A, ZHU M, et al. MobileNetV2: Inverted Residuals and Linear Bottlenecks [C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 4510-4520.
|
17 |
CHU J, GUO Z, LENG L. Object detection based on multi-layer convolution feature fusion and online hard example mining. IEEE Access, 2018, 19959- 19967.
|
18 |
IOFFE S, SZEGEDY C. Batch normalization: accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the 32nd International Conference on Machine Learning. 2015: 448-456.
|
19 |
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. 2017: 2755-2763.
|
20 |
GOU J P, YU B S, MAYBANK S J, et al. Knowledge distillation: A survey [EB/OL]. (2020-06-09)[2021-06-12]. https://arxiv.org/abs/2006.05525.
|
21 |
MEHTA R, OZTURK C. Object detection at 200 frames per second [EB/OL]. (2018-05-16)[2021-06-12]. https://arxiv.org/abs/1805.06361.
|