80 citations · 161 across the 6 of their papers we have counts for
6 papers
Three-dimensional Damage Visualization of Civil Structures via Gaussian Splatting-enabled Digital Twins
Shuo Wang, Xin Nie, Yasutaka Narazaki +2
Recent advancements in civil infrastructure inspections underscore the need for precise three-dimensional (3D) damage visualization on digital twins, transcending traditional 2D im…
Towards Automated Post-Earthquake Inspections with Deep Learning-based Condition-Aware Models
Vedhus Hoskere, Yasutaka Narazaki, Tu A. Hoang +1
In the aftermath of an earthquake, rapid structural inspections are required to get citizens back in to their homes and offices in a safe and timely manner. These inspections gfare…
Automated Bridge Component Recognition using Video Data
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
This paper investigates the automated recognition of structural bridge components using video data. Although understanding video data for structural inspections is straightforward…
Automated Vision-based Bridge Component Extraction Using Multiscale Convolutional Neural Networks
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
Image data has a great potential of helping post-earthquake visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing v…
Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
Image data has a great potential of helping conventional visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visu…
Vision-based Structural Inspection using Multiscale Deep Convolutional Neural Networks
Vedhus Hoskere, Yasutaka Narazaki, Tu Hoang +1
Current methods of practice for inspection of civil infrastructure typically involve visual assessments conducted manually by trained inspectors. For post-earthquake structural ins…