2021
DOI: 10.1061/(asce)cf.1943-5509.0001594
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Data Augmentation for Improving Deep Learning Models in Building Inspections or Postdisaster Evaluation

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Cited by 9 publications
(2 citation statements)
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References 64 publications
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“…While various ML theories and techniques have been adopted in CE, few TL studies have been conducted (Azimi & Pekcan, 2020; Luo & Paal, 2021; Pak & Paal, 2022). Furthermore, the majority are focused on image‐based models (Cha et al., 2017; Cheng et al., 2021; Leach et al., 2021; Li et al., 2019).…”
Section: Related Workmentioning
confidence: 99%
“…While various ML theories and techniques have been adopted in CE, few TL studies have been conducted (Azimi & Pekcan, 2020; Luo & Paal, 2021; Pak & Paal, 2022). Furthermore, the majority are focused on image‐based models (Cha et al., 2017; Cheng et al., 2021; Leach et al., 2021; Li et al., 2019).…”
Section: Related Workmentioning
confidence: 99%
“…The other 26 articles focused on the detailed inspection of an individual building. Damages can be detected from UAV images through manual judgement [17,18], digital image processing (DIP) [2,19] and deep learning (DL) [3,20] algorithms. Besides, building damage and damage volume can be estimated based on the point cloud and the 3D model generated through image-based 3D reconstruction [21,22].…”
Section: Uav For Visual Building Inspectionmentioning
confidence: 99%