HIGHLIGHTS
- who: Pengcheng Zhu and colleagues from the Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, China Department of Physics, University of Fribourg, Fribourg, Switzerland have published the Article: Object Detection for Hazardous Material Vehicles Based on Improved YOLOv5 Algorithm, in the Journal: Electronics 2023, 12, 1257. of /2023/
- what: In this paper, an algorithm based on an improved YOLOv5 model is proposed for the detection of hazardous chemical vehicles. YOLOv5 uses the CSP-Darknet53 network as the backbone of the model, which is mainly composed of modules such as Focus, Convolution block . . .
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