collaborators

5 papers

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

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…