Lightweight Design of Hardhat Wearing Detection Based on Deep Learning-Reference-Cited by-同舟云学术

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Lightweight Design of Hardhat Wearing Detection Based on Deep Learning

Published:2023-11-30 Issue: Volume:2004 Page:982-992
ISSN:
Container-title:ICCREM 2023
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Author:

Zhang Guiying¹²³¹⁴,Yang Liqiong¹²³¹⁴,Hu Wenjun¹²³¹⁴,Yang Hang¹²³¹⁴,Xiao Yufeng¹²³¹⁴

Affiliation:

1. School of Civil Engineering and Architecture, Southwest Univ. of Science and Technology, Mianyang, China.

2. Professor, School of Civil Engineering and Architecture, Southwest Univ. of Science and Technology, Mianyang, China (corresponding author).

3. School of Information Engineering, Southwest Univ. of Science and Technology, Mianyang, China.

4. Professor, School of Information Engineering, Southwest Univ. of Science and Technology, Mianyang, China.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485217.097

Reference21 articles.

1. Lightweight and computationally faster Hypermetropic Convolutional Neural Network for small size object detection

2. Yolov4: Optimal speed and accuracy of object detection;Bochkovskiy A.;arXiv,2020

3. A deep learning-based ensemble method for helmet-wearing detection

4. Object Detection Related to Irregular Behaviors of Substation Personnel Based on Improved YOLOv4

5. Rich feature hierarchies for accurate object detection and semantic segmentation;Girshick R.;Proceedings of the IEEE conference on computer vision and pattern recognition,2014

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