Structural damage detection from wavelet packet sensitivity

By Siu-seong Law, X. Y. Li, Xinqun Zhu, Siu-Lai Chan. 2005

150 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/0f93e6d9da31da867fdf135634d66e33ea88e27b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Hongwei Ma
2. Zhen-Hua Nie
3. Yi-Zhou Lin

In Computer Vision and Pattern Recognition

1. Hongwei Ma
2. Zhen-Hua Nie
3. Yi-Zhou Lin

Citations in the corpus

• Structural Damage Detection with Automatic Feature‐Extraction through Deep Learning (2017, methodology): “Some new techniques of deep learning proposed by recent studies are used to improve its performance, resulting in an excellent accuracy, which is better than using wavelet packet transform component energy (Law et al., 2005) as the input feature.”