Synchrosqueezed wavelet transform-fractality model for locating, detecting, and quantifying damage in smart highrise building structures

By Juan Pablo Amezquita-Sanchez, Hojjat Adeli. 2015

171 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Geophysics

View Paper: https://www.semanticscholar.org/paper/a7c50d8f9cba8945029cb44ce9394c1148f60fa8

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. Shengyuan Li
2. Guangyi Zhou
3. Xuefeng Zhao

In Computer Vision and Pattern Recognition

1. Shengyuan Li
2. Guangyi Zhou
3. Xuefeng Zhao

In Geophysics

1. Shengyuan Li
2. Guangyi Zhou
3. Xuefeng Zhao

Citations in the corpus

• Automatic pixel‐level multiple damage detection of concrete structure using fully convolutional network (2019, methodology): “To improve the adaptability of IPTs-based methods in real-world situations, machine learning (ML)-based approaches are used to conduct feasible solutions to damage detection (Amezquita-Sanchez & Adeli, 2015; Butcher et al., 2014; Jiang & Adeli, 2007).”