• Optoelectronics Letters
  • Vol. 21, Issue 1, 35 (2025)
Dongdong GUI and Bo SUN
DOI: 10.1007/s11801-025-3245-3 Cite this Article
GUI Dongdong, SUN Bo. Traffic safety helmet wear detection based on improved YOLOv5 network[J]. Optoelectronics Letters, 2025, 21(1): 35 Copy Citation Text show less
References

[1] ESPINOSA J E, VELASTIN S A, BRANCH J W. Detection of motorcycles in urban traffic using video analysis: a review[J]. IEEE transactions on intelligent transportation systems, 2020, 22(10): 6115-6130.

[2] SUGIARTO R, SUSANTO E K, KRISTIAN Y. Helmet usage detection on motorcyclist using deep residual learning[C]//2021 3rd East Indonesia Conference on Computer and Information Technology, April 9-11, 2021, Surabaya, Indonesia. New York: IEEE, 2021: 194-198.

[3] HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 770-778.

[4] MISTRY J, MISRAA A K, AGARWAL M, et al. An automatic detection of helmeted and non-helmeted motorcyclist with license plate extraction using convolutional neural network[C]//2017 7th International Conference on Image Processing Theory, Tools and Applications, November 28-December 1, 2017, Montreal, QC, Canada. New York: IEEE, 2017: 1-6.

[5] LIN T Y, MAIRE M, BELONGIE S, et al. Microsoft coco: common objects in context[C]//Proceedings of the European Conference on Computer Vision (ECCV), September 6-12, 2014, Zurich, Switzerland. Heidelberg: Springer International Publishing, 2014: 740-755.

[6] DASGUPTA M, BANDYOPADHYAY O, CHATTERJI S. Automated helmet detection for multiple motorcycle riders using CNN[C]//2019 IEEE Conference on Information and Communication Technology, December 6-8, 2019, Allahabad, India. New York: IEEE, 2019: 1-4.

[7] LI C H, HUANG D. Detecting helmets on motorcyclists by deep neural networks with a dual-detection scheme[C]//28th International Conference on Neural Information Processing, December 8-12, 2021, Sanur, Bali, Indonesia. Heidelberg: Springer International Publishing, 2021: 417-427.

[8] LI Z, XIE W, ZHANG L, et al. Toward efficient safety helmet detection based on YOLOv5 with hierarchical positive sample selection and box density filtering[J]. IEEE transactions on instrumentation and measurement, 2022, 71: 1-14.

[9] LIU Y, SHI G, LI Y, et al. M-YOLO: traffic sign detection algorithm applicable to complex scenarios[J]. Symmetry, 2022, 14(5): 952.

[10] CHARRAN R S, DUBEY R K. Two-wheeler vehicle traffic violations detection and automated ticketing for Indian road scenario[J]. IEEE transactions on intelligent transportation systems, 2022, 23(11): 22002-22007.

[11] FARID A, HUSSAIN F, KHAN K, et al. A fast and accurate real-time vehicle detection method using deep learning for unconstrained environments[J]. Applied sciences, 2023, 13(5): 3059.

[12] CHENG R, HE X, ZHENG Z, et al. Multi-scale safety helmet detection based on SAS-YOLOv3-tiny[J]. Applied sciences, 2021, 11(8): 3652.

[13] LIU S, KONG W, CHEN X, et al. Multi-scale ship detection algorithm based on a lightweight neural network for spaceborne SAR images[J]. Remote sensing, 2022, 14(5): 1149.

[14] 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, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 2018: 4510-4520.

[15] LI S, FU X, DONG J. Improved ship detection algorithm based on YOLOX for SAR outline enhancement image[J]. Remote sensing, 2022, 14(16): 4070.

[16] GE Z, LIU S, WANG F, et al. YOLOX: exceeding YOLO series in 2021[EB/OL]. (2021-07-18) [2023-5-26]. https://arxiv.org/abs/2107.08430.

[17] HAN K, WANG Y, TIAN Q, et al. Ghostnet: more features from cheap operations[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 13-19, 2020, Seattle, WA, USA. New York: IEEE, 2020: 1580-1589.

[18] XIAO B, YAN C. A lightweight global awareness deep network model for flame and smoke detection[J]. Optoelectronics letters, 2023, 19(10): 614-622.

[19] TARG S, ALMEIDA D, LYMAN K. Resnet in Resnet: generalizing residual architectures[EB/OL]. (2016-03-25) [2023-5-26]. ahttps://arxiv.org/abs/1603.08029.

[20] LIU X Y, GUO C Y, GONG Z H, et al. Object detection in remote sensing image with improved RFB net[J]. Journal of geomatics science and technology, 2019, 36(2): 179-184.