HR-YOLO: Segmentation and detection of emergency escape ramp scenes using an integrated HR-net and improved YOLOv12 model

The proposed approach provides an efficient and reliable technological solution for the intelligent recognition of key infrastructure in traffic safety monitoring systems.

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Publication Details

Journal
Traffic Injury Prevention
Published
2025-10-15
DOI
https://doi.org/10.1080/15389588.2025.2557513
Citations
2
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
2.55
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article

HR-YOLO: Segmentation and detection of emergency escape ramp scenes using an integrated HR-net and improved YOLOv12 model

Haozhi Zhang, Zhao-Long Hu, Guiling Li
2 citations
Traffic Injury Prevention
Advanced Neural Network Applications
2.55
article

HR-YOLO: Segmentation and detection of emergency escape ramp scenes using an integrated HR-net and improved YOLOv12 model

Haozhi Zhang, Zhao-Long Hu, Guiling Li
article en
2 citations

Abstract

The proposed approach provides an efficient and reliable technological solution for the intelligent recognition of key infrastructure in traffic safety monitoring systems.

Traffic Injury Prevention
University of Shanghai for Science and Technology (CN), Henan Normal University (CN)
Openalex Percentile: Top 9%
Advanced Neural Network Applications
2.55
DOISourceOpenAlex
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HR-YOLO: Segmentation and detection of emergency escape ramp scenes using an integrated HR-net and improved YOLOv12 model — Haozhi Zhang, Zhao-Long Hu, et al. · Traffic Injury Prevention (2025) | TGRS Research Map | TGRS