Tactile Paving Recognition Method Based on Improved YOLOv7

Tactile paving is a professional road facility to ensure the safe travel of people with visual impairment. However, there are many problems with tactile paving travel in practice. For one, some tactile paving is seriously damaged, and the other is the accumulation of obstacles. How to help visually impaired people recognize and locate obstacles in tactile paving is a problem worth studying. In this paper, image recognition technology is used to recognize the tactile paving pictures with obstacles, and an attention mechanism is used to optimize samples to improve recognition accuracy.

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Publication Details

Journal
Journal of Electronic Research and Application
Published
2024-08-12
DOI
https://doi.org/10.26689/jera.v8i4.7920
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.35
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article

Tactile Paving Recognition Method Based on Improved YOLOv7

Qun Chao Zhao, Nan Fang, Chengyi Shi, Yufeng Mao
1 citations
Journal of Electronic Research and Application
Industrial Vision Systems and Defect Detection
0.35
article

Tactile Paving Recognition Method Based on Improved YOLOv7

Qun Chao Zhao, Nan Fang, Chengyi Shi, Yufeng Mao
article en
1 citations

Abstract

Tactile paving is a professional road facility to ensure the safe travel of people with visual impairment. However, there are many problems with tactile paving travel in practice. For one, some tactile paving is seriously damaged, and the other is the accumulation of obstacles. How to help visually impaired people recognize and locate obstacles in tactile paving is a problem worth studying. In this paper, image recognition technology is used to recognize the tactile paving pictures with obstacles, and an attention mechanism is used to optimize samples to improve recognition accuracy.

Journal of Electronic Research and ApplicationVol. 8(4)
Nanjing Institute of Technology (CN), China Electric Equipment Group (China) (CN)
Sustainable cities and communities
Openalex Percentile: Top 37%
Industrial Vision Systems and Defect Detection
0.35
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