期刊论文

Tianyong Jiang

英文

Journal of Civil Structural Health Monitoring

2190-5452

2024

1-22

10.1007/s13349-024-00798-6

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: the authors acknowledge financial support from the National Natural Science Foundation of China (Grant Nos. 52078058, 52378123), the Natural Science Foundation for Creative Research Groups of Hunan Province, China (Grant No. 2020JJ1006), the Scientific Research Fund of Hunan Provincial Education Department, China (Grant No. 21A0196), the Postgraduate Research Innovation Project of Hunan Province (Grant No. CX20220879) and the Natural Science Foundation of Changsha City, China (Grant No. kq2202209). This support is gratefully acknowledged.

本校为第一且通讯机构

This paper proposes a new complex background segmentation method based on the modified fully convolutional network semantic segmentation for noncontact cable vibration frequency estimation. The estimation of frequency from video data is challenged by the presence of background object motion, which directly impacts the accuracy of the video-based method. To address this issue, image tests were carried out among the existing model (U2-Net) to explore the effect of the efficient channel attention (ECA) and convolutional block attention module (CBAM) on cable segmentation performance. As a result,...