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Automatic detection method of cracks from concrete surface imagery using two‐step light gradient boosting machine

Computer-aided civil and infrastructure engineering, 2021-01, Vol.36 (1), p.61-72

2021

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A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage

Computer-aided civil and infrastructure engineering, 2022-09, Vol.37 (11), p.1387-1401

2022

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Crack Detection from a Concrete Surface Image Based on Semantic Segmentation Using Deep Learning

Journal of Advanced Concrete Technology, 2020/09/16, Vol.18(9), pp.493-504

2020

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Development of a Concrete Floating and Delamination Detection System Using Infrared Thermography

IEEE/ASME transactions on mechatronics, 2021-12, Vol.26 (6), p.2835-2844

2021

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Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network

Computer-aided civil and infrastructure engineering, 2024-02, Vol.39 (4), p.575-594

2024

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Applicability of machine learning to a crack model in concrete bridges

Computer-aided civil and infrastructure engineering, 2020-08, Vol.35 (8), p.775-792

2020

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Study on Accuracy Improvement of Slope Failure Region Detection Using Mask R-CNN with Augmentation Method

Sensors (Basel, Switzerland), 2022-08, Vol.22 (17), p.6412

2022

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Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results

Computer-aided civil and infrastructure engineering, 2023-11, Vol.38 (17), p.2391-2407

2023

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Improving visual question answering for bridge inspection by pre‐training with external data of image–text pairs

Computer-aided civil and infrastructure engineering, 2024-02, Vol.39 (3), p.345-361

2024

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Random forest-based evaluation technique for internal damage in reinforced concrete featuring multiple nondestructive testing results

Construction & building materials, 2020-08, Vol.253, p.119238, Article 119238

2020

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ViTALnet: Anomaly on Industrial Textured Surfaces With Hybrid Transformer

IEEE transactions on instrumentation and measurement, 2023, Vol.72, p.1-13

2023

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Development of a Machine Learning-Based Damage Identification Method Using Multi-Point Simultaneous Acceleration Measurement Results

Sensors (Basel, Switzerland), 2020-05, Vol.20 (10), p.2780

2020

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Self‐training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation

Computer-aided civil and infrastructure engineering, 2024-09, Vol.39 (17), p.2642-2661

2024

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Cascade refinement extraction network with active boundary loss for segmentation of concrete cracks from high-resolution images

Automation in construction, 2024-06, Vol.162, p.105410, Article 105410

2024

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Automatic Detection of Cracks in Asphalt Pavement Using Deep Learning to Overcome Weaknesses in Images and GIS Visualization

Applied sciences, 2021-02, Vol.11 (3), p.892

2021

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Development of an action classification method for construction sites combining pose assessment and object proximity evaluation

Journal of ambient intelligence and humanized computing, 2024-04, Vol.15 (4), p.2255-2267

2024

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The Cover Depth Effect on Corrosion-Induced Deterioration of Reinforced Concrete Focusing on Water Penetration: Field Survey and Laboratory Study

Materials, 2021-06, Vol.14 (13), p.3478

2021

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Surrogate Model Development for Slope Stability Analysis Using Machine Learning

Sustainability, 2023-07, Vol.15 (14), p.10793

2023

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Evaluation of Tensile Performance of Steel Members by Analysis of Corroded Steel Surface Using Deep Learning

Metals (Basel ), 2019-12, Vol.9 (12), p.1259

2019

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Corrosion Damage Detection in Headrace Tunnel Using YOLOv7 with Continuous Wall Images

Applied sciences, 2023-08, Vol.13 (16), p.9388

2023

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Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks

Shock and vibration, 2015-01, Vol.2015 (2015), p.1-11

2015

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Artificial Neural Network for Vertical Displacement Prediction of a Bridge from Strains (Part 1): Girder Bridge under Moving Vehicles

Applied sciences, 2019-07, Vol.9 (14), p.2881

2019

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Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections

Journal of robotics and mechatronics, 2020-12, Vol.32 (6), p.1244-1258

2020

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Undersampling Strategy for Machine-learned Deterioration Regression Model in Concrete Bridges

Journal of Advanced Concrete Technology, 2020/12/19, Vol.18(12), pp.753-766

2020

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Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach

Advanced robotics, 2021-06, Vol.35 (11), p.715-722

2021

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Automatic detection method of cracks from concrete surface imagery using two‐step light gradient boosting machine

A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage

Crack Detection from a Concrete Surface Image Based on Semantic Segmentation Using Deep Learning

Development of a Concrete Floating and Delamination Detection System Using Infrared Thermography

Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network

Applicability of machine learning to a crack model in concrete bridges

Study on Accuracy Improvement of Slope Failure Region Detection Using Mask R-CNN with Augmentation Method

Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results

Improving visual question answering for bridge inspection by pre‐training with external data of image–text pairs

Random forest-based evaluation technique for internal damage in reinforced concrete featuring multiple nondestructive testing results

ViTALnet: Anomaly on Industrial Textured Surfaces With Hybrid Transformer

Development of a Machine Learning-Based Damage Identification Method Using Multi-Point Simultaneous Acceleration Measurement Results

Self‐training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation

Cascade refinement extraction network with active boundary loss for segmentation of concrete cracks from high-resolution images

Automatic Detection of Cracks in Asphalt Pavement Using Deep Learning to Overcome Weaknesses in Images and GIS Visualization

Development of an action classification method for construction sites combining pose assessment and object proximity evaluation

The Cover Depth Effect on Corrosion-Induced Deterioration of Reinforced Concrete Focusing on Water Penetration: Field Survey and Laboratory Study

Surrogate Model Development for Slope Stability Analysis Using Machine Learning

Evaluation of Tensile Performance of Steel Members by Analysis of Corroded Steel Surface Using Deep Learning

Corrosion Damage Detection in Headrace Tunnel Using YOLOv7 with Continuous Wall Images

Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks

Artificial Neural Network for Vertical Displacement Prediction of a Bridge from Strains (Part 1): Girder Bridge under Moving Vehicles

Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections

Undersampling Strategy for Machine-learned Deterioration Regression Model in Concrete Bridges

Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach

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