2 citations · 2 across the 5 of their papers we have counts for
5 papers
Deep learning-based automated damage detection in concrete structures using images from earthquake events
Abdullah Turer, Yongsheng Bai, Halil Sezen +1
Timely assessment of integrity of structures after seismic events is crucial for public safety and emergency response. This study focuses on assessing the structural damage conditi…
Engineering deep learning methods on automatic detection of damage in infrastructure due to extreme events
Yongsheng Bai, Bing Zha, Halil Sezen +1
This paper presents a few comprehensive experimental studies for automated Structural Damage Detection (SDD) in extreme events using deep learning methods for processing 2D images.…
Automatic Displacement and Vibration Measurement in Laboratory Experiments with A Deep Learning Method
Yongsheng Bai, Ramzi M. Abduallah, Halil Sezen +1
This paper proposes a pipeline to automatically track and measure displacement and vibration of structural specimens during laboratory experiments. The latest Mask Regional Convolu…
A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse
Ningli Xu, Debao Huang, Shuang Song +5
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a b…
End-to-end Deep Learning Methods for Automated Damage Detection in Extreme Events at Various Scales
Yongsheng Bai, Halil Sezen, Alper Yilmaz
Robust Mask R-CNN (Mask Regional Convolu-tional Neural Network) methods are proposed and tested for automatic detection of cracks on structures or their components that may be dama…