journal article·2024Open access

An Improved Distraction Behavior Detection Algorithm Based on YOLOv5

Keke Zhou, Guoqiang Zheng, Huihui Zhai, Xiangshuai Lv, Weizhen Zhang

Computers, Materials & Continua· Volume 81· Issue 2

Abstract

Distracted driving remains a primary factor in traffic accidents and poses a significant obstacle to advancing driver assistance technologies. Improving the accuracy of distracted driving can greatly reduce the occurrence of ... | Find, read and cite all the research you need on Tech Science Press
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Research context

OpenAlex topics: IoT-based Smart Home Systems

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References (30)

Show source-provided references
1. Dangerous and aggressive driving: Detecting the interrelationship by data mining10.1007/s40996-021-00712-w ↗
2. Road safety and distraction, results from a responsibility case-control study among a sample of road users interviewed at the emergency room10.1016/j.aap.2018.09.032 ↗
3. Classification of distracted driving based on visual features and behavior data using a random forest method10.1177/0361198118796963 ↗
4. Driver distraction detection methods: A literature review and framework10.1109/ACCESS.2021.3073599 ↗
5. Driver behavior detection via adaptive spatial attention mechanism10.1016/j.aei.2021.101280 ↗
6. Effect of cognitive distraction on physiological measures and driving performance in traditional and mixed traffic environments10.1155/2021/6739071 ↗
7. Real-time detection system of driver distraction using machine learning10.1109/TITS.2013.2247760 ↗
8. Driver behavior detection and classification using deep convolutional neural networks10.1016/j.eswa.2020.113240 ↗
9. Detection of driver vigilance level using EEG signals and driving contexts10.1109/TR.2017.2778754 ↗
10. Driver distraction detection using bidirectional long short-term network based on multiscale entropy of EEG10.1109/TITS.2022.3159602 ↗
11. HSDDD: A hybrid scheme for the detection of distracted driving through fusion of deep learning and handcrafted features10.3390/s22051864 ↗
12. Distracted driving detection based on the fusion of deep learning and causal reasoning10.1016/j.inffus.2022.08.009 ↗
13. CEAM-YOLOv7: Improved YOLOv7 based on channel expansion and attention mechanism for driver distraction behavior detection10.1109/ACCESS.2022.3228331 ↗
14. AB-DLM: An improved deep learning model based on attention mechanism and BiFPN for driver distraction behavior detection10.1109/ACCESS.2022.3197146 ↗
15. Detection of distracted driving via edge artificial intelligence10.1016/j.compeleceng.2023.108951 ↗
16. An efficient deep learning framework for distracted driver detection10.1109/ACCESS.2021.3138137 ↗
17. A novel driver distraction behavior detection method based on self-supervised learning with masked image modeling10.1109/JIOT.2023.3308921 ↗
18. A proactive recognition system for detecting commercial vehicle driver’s distracted behavior
19. Driver distraction detection using machine learning algorithms: An experimental approach10.1504/IJVD.2020.115057 ↗
20. Driver drowsiness detection and alert system development using object detection10.18280/ts.390211 ↗
21. Distracted driver detection based on a CNN with decreasing filter size10.1109/TITS.2021.3063521 ↗
22. Detection of distracted driving based on MultiGranularity and middle-level features
23. Driving fatigue detection based on the combination of multi-branch 3D-CNN and attention mechanism10.3390/app12094689 ↗
24. HCF: A hybrid CNN framework for behavior detection of distracted drivers10.1109/ACCESS.2020.3001159 ↗
25. Driver attention detection based on improved YOLOv5
26. A comparative study of YOLOv5 and YOLOv7 object detection algorithms10.33736/jcsi.5070.2023 ↗
27. Research on object detection algorithm based on improved yolov5
28. Ultralytics/yolov5:v3.1-bug fixes and performance improvements
29. YOLOX: Exceeding YOLO series in 2021
30. Feature refinement for image-based driver action recognition via multi-scale attention convolutional neural network