4.7 Article

Attention-based generative adversarial network with internal damage segmentation using thermography

Related references

Note: Only part of the references are listed.
Article Construction & Building Technology

Detection of delamination and rebar debonding in concrete structures with ultrasonic SH-waveform tomography

Ruoyu Chen et al.

Summary: This paper presents a novel application of 2D fullwaveform inversion of ultrasonic SH-waves for detection of delamination and rebar debonding in concrete structures, providing accurate location and characterization of delaminations and identification of rebar debonding. The SH-FWI method offers clearer structural images with more detailed information compared to traditional techniques such as SAFT.

AUTOMATION IN CONSTRUCTION (2022)

Article Computer Science, Artificial Intelligence

InfraGAN: A GAN architecture to transfer visible images to infrared domain

Mehmet Akif Ozkanoglu et al.

Summary: This paper introduces a solution based on generative adversarial networks (GAN) to generate the infrared equivalent of a given visible image. The proposed method achieves better performance in terms of structural similarity and other metrics compared to existing architectures.

PATTERN RECOGNITION LETTERS (2022)

Article Engineering, Multidisciplinary

Instant bridge visual inspection using an unmanned aerial vehicle by image capturing and geo-tagging system and deep convolutional neural network

Muhammad Rakeh Saleem et al.

Summary: This paper proposes an instant damage identification and localization approach using an image capturing and geo-tagging system and deep convolutional neural network for crack detection. The method allows for automatic generation of a global bridge damage map using images captured and geo-tagged with three-dimensional coordinates and camera pose data.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2021)

Article Construction & Building Technology

Real-time multiple damage mapping using autonomous UAV and deep faster region-based neural networks for GPS-denied structures

Rahmat Ali et al.

Summary: An autonomous UAV system with a modified Faster R-CNN was proposed for identifying structural damage and mapping it in a GPS-denied environment. The method significantly reduced false positives, especially in detecting small cracks in blurry videos caused by UAV vibrations. In real-world tests, the autonomous UAV successfully followed desired trajectories and accurately detected defects using Faster R-CNN.

AUTOMATION IN CONSTRUCTION (2021)

Article Construction & Building Technology

Thermal anomaly detection in walls via CNN-based segmentation

Gwanyong Park et al.

Summary: This study developed an automatic anomaly detection framework for detecting thermal anomalies of a building envelope, by segmenting the wall from visible images and determining the temperature threshold of the anomaly area based on the multimodal temperature distribution of the target domain. The performance of anomaly detection was improved significantly by applying the segmentation process.

AUTOMATION IN CONSTRUCTION (2021)

Article Construction & Building Technology

Automated subsurface defects' detection using point cloud reconstruction from infrared images

Marco Puliti et al.

Summary: The research introduces a novel inspection technique combining SfM algorithms and infrared imaging for detecting subsurface defects and quantifying their severity and dimensions. Experimental results show that the method has an error below 5% and can easily be integrated into unmanned aerial vehicles for remote inspection and damage detection.

AUTOMATION IN CONSTRUCTION (2021)

Article Construction & Building Technology

Image-based concrete crack detection in tunnels using deep fully convolutional networks

Yupeng Ren et al.

CONSTRUCTION AND BUILDING MATERIALS (2020)

Article Construction & Building Technology

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection

Qiaoning Yang et al.

AUTOMATION IN CONSTRUCTION (2020)

Article Construction & Building Technology

An integrated approach to automatic pixel-level crack detection and quantification of asphalt pavement

Ankang Ji et al.

AUTOMATION IN CONSTRUCTION (2020)

Article Computer Science, Interdisciplinary Applications

UNet plus plus : Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

Zongwei Zhou et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Construction & Building Technology

Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning

Dongho Kang et al.

AUTOMATION IN CONSTRUCTION (2020)

Article Automation & Control Systems

SDDNet: Real-Time Crack Segmentation

Wooram Choi et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

Review Construction & Building Technology

Comprehensive Inspection System for Concrete Bridge Deck Application: Current Situation and Future Needs

Sherif Abdelkhalek et al.

JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES (2020)

Article Construction & Building Technology

A spatial-channel hierarchical deep learning network for pixel-level automated crack detection

Yue Pan et al.

AUTOMATION IN CONSTRUCTION (2020)

Article Construction & Building Technology

Deep learning-based automatic volumetric damage quantification using depth camera

Gustavo H. Beckman et al.

AUTOMATION IN CONSTRUCTION (2019)

Article Construction & Building Technology

Autonomous concrete crack detection using deep fully convolutional neural network

Cao Vu Dung et al.

AUTOMATION IN CONSTRUCTION (2019)

Article Construction & Building Technology

Subsurface damage detection of a steel bridge using deep learning and uncooled micro-bolometer

Rahmat Ali et al.

CONSTRUCTION AND BUILDING MATERIALS (2019)

Article Engineering, Civil

Two-tier data fusion method for bridge condition assessment

Marwa Ahmed et al.

CANADIAN JOURNAL OF CIVIL ENGINEERING (2018)

Article Computer Science, Interdisciplinary Applications

Autonomous UAVs for Structural Health Monitoring Using Deep Learning and an Ultrasonic Beacon System with Geo-Tagging

Dongho Kang et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)

Article Computer Science, Interdisciplinary Applications

Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

Young-Jin Cha et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2018)

Article Instruments & Instrumentation

Air-coupled impact-echo damage detection in reinforced concrete using wavelet transforms

Tyler Epp et al.

SMART MATERIALS AND STRUCTURES (2017)

Article Construction & Building Technology

Performance of NDT Techniques in Appraising Condition of Reinforced Concrete Bridge Decks

Tarek Omar et al.

JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES (2017)

Article Construction & Building Technology

Concrete bridge deck condition assessment using IR Thermography and Ground Penetrating Radar technologies

Saleh Abu Dabous et al.

AUTOMATION IN CONSTRUCTION (2017)

Article Computer Science, Interdisciplinary Applications

Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks

Young-Jin Cha et al.

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2017)

Article Computer Science, Artificial Intelligence

Multi-modal RGB-Depth-Thermal Human Body Segmentation

Cristina Palmero et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2016)

Article Engineering, Civil

Nondestructive Bridge Deck Testing with Air-Coupled Impact-Echo and Infrared Thermography

Seong-Hoon Kee et al.

JOURNAL OF BRIDGE ENGINEERING (2012)

Review Engineering, Civil

Acoustic emission monitoring of bridges: Review and case studies

Archana Nair et al.

ENGINEERING STRUCTURES (2010)

Article Engineering, Civil

Effects of Environmental Variables on Infrared Imaging of Subsurface Features of Concrete Bridges

Glenn Washer et al.

TRANSPORTATION RESEARCH RECORD (2009)

Article Construction & Building Technology

Innovative process to characterize buried utilities using Ground Penetrating Radar

Jim Lester et al.

AUTOMATION IN CONSTRUCTION (2007)

Article Engineering, Civil

Detection of common defects in concrete bridge decks using nondestructive evaluation techniques

Sherif Yehia et al.

JOURNAL OF BRIDGE ENGINEERING (2007)

Article Materials Science, Characterization & Testing

A comparison of nondestructive evaluation methods for bridge deck assessment

M Scott et al.

NDT & E INTERNATIONAL (2003)