One-Shot Monitoring Approach for Construction Workers’ Hardhats Based on Siamese Networks
Author:
Affiliation:
1. Ph.D. Student, Dept. of Architecture and Architectural Engineering, Yonsei Univ. ORCID: .
2. Professor, Dept. of Architecture and Architectural Engineering, Yonsei Univ. . ORCID: .
Publisher
American Society of Civil Engineers
Link
https://ascelibrary.org/doi/pdf/10.1061/9780784485248.063
Reference16 articles.
1. Few-shot classification of façade defects based on extensible classifier and contrastive learning
2. Du S. M. Shehata and W. Badawy. 2011. “Hard hat detection in video sequences based on face features motion and color information.” 2011 3rd International Conference on Computer Research and Development 25–29.
3. Detecting non-hardhat-use by a deep learning method from far-field surveillance videos
4. Detecting Construction Equipment Using a Region-Based Fully Convolutional Network and Transfer Learning
5. A few-shot learning approach for database-free vision-based monitoring on construction sites
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