[1] |
李夕兵,杜晶,洪亮. 工业安全帽的抗冲击性能[J]. 中南大学学报(自然科学版), 2011,42(6):1692-1697.
|
[2] |
王思甜,赵禹平,刘云飞. 基于图像处理的城市智能化交通系统设计[J]. 科技与创新, 2019(9):42-44.
|
[3] |
黄凯奇,陈晓棠,康运锋,等. 智能视频监控技术综述[J]. 计算机学报, 2015,38(6):1093-1118.
|
[4] |
陈学斌. 基于人工智能的工业互联网生产设备故障检测研究[J]. 信息通信, 2020(8):143-144.
|
[5] |
杨露,牛燕雄,张颖,等. 星载光电成像系统空间目标的检测与识别技术研究[J]. 激光与光电子学进展, 2014,51(12):112-118.
|
[6] |
冯国臣,陈艳艳,陈宁,等. 基于机器视觉的安全帽自动识别技术研究[J]. 机械设计与制造工程, 2015,44(10):39-42.
|
[7] |
刘晓慧,叶西宁. 肤色检测和Hu矩在安全帽识别中的应用[J]. 华东理工大学学报(自然科学版), 2014,40(3):365-370.
|
[8] |
周艳青,薛河儒,姜新华,等. 基于LBP统计特征的低分辨率安全帽识别[J]. 计算机系统应用, 2015,24(7):211-215.
|
[9] |
林俊,党伟超,潘理虎,等. 基于YOLO的安全帽检测方法[J]. 计算机系统应用, 2019,28(9):174-179.
|
[10] |
REDMON J, DIVVALA S, GIRSHICK R, et al. You only look once: Unified, real-time object detection[C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. 2016:779-788.
|
[11] |
施辉,陈先桥,杨英. 改进YOLOv3的安全帽佩戴检测方法[J]. 计算机工程与应用, 2019,55(11):213-220.
|
[12] |
REDMON J, FARHADI A. YOLOv3: An incremental improvement[J]. arXiv preprint arXiv:1804.02767, 2018.
|
[13] |
吴冬梅,王慧,李佳. 基于改进Faster RCNN的安全帽检测及身份识别[J]. 信息技术与信息化, 2020(1):17-20.
|
[14] |
吴红兵,杨道朋,赵兵,等. 基建现场视频监控系统的应用及关键技术研究[J]. 中国新通信, 2019,21(24):111.
|
[15] |
BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: Optimal speed and accuracy of object detection[J]. arXiv preprint arXiv:2004.10934, 2020.
|
[16] |
LIU W, ANGUELOV D, ERHAN D, et al. SSD: Single shot multiBox detector[C]// 2016 European Conference on Computer Vision. 2016:21-37.
|
[17] |
LIN T Y, GOYAL P, GIRSHICK R, et al. Focal loss for dense object detection[C]// Proceedings of the 2017 IEEE International Conference on Computer Vision. 2017:2999-3007.
|
[18] |
REDMON J, FARHADI A. YOLO9000: Better, faster, stronger[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. 2017:6517-6525.
|
[19] |
YU J H, JIANG Y N, WANG Z Y, et al. UnitBox: An advanced object detection network[C]// Proceedings of the 24th ACM International Conference on Multimedia. 2016:516-520.
|
[20] |
WANG C Y, LIAO H Y M, WU Y H, et al. CSPNet: A new backbone that can enhance learning capability of CNN[C]// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2020:1571-1580.
|
[21] |
LIU S, QI L, QIN H F, et al. Path aggregation network for instance segmentation[C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2018:8759-8768.
|
[22] |
GHIASI G, LIN T Y, LE Q V. DropBlock: A regularization method for convolutional networks[C]// Proceedings of the 32nd International Conference on Neural Information Processing Systems. 2018:10750-10760.
|
[23] |
HU J, SHEN L, SUN G. Squeeze-and-excitation networks[C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2018:7132-7141.
|
[24] |
ZHENG Z H, WANG P, LIU W, et al. Distance-IoU loss: Faster and better learning for bounding box regression[C]// Proceedings of the 2020 AAAI Conference on Artificial Intelligence. 2020,34(7):12993-13000.
|