Yun-Kyu An

Assistant Professor

Sejong University

South Korea

Research Interests

Explore related searches

Professors in South Korea Professors in Civil Engineering Civil Engineering professors in South Korea

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Yun-Kyu An is an Assistant Professor at Sejong University in South Korea. His research areas include deep learning applications in civil engineering, with a focus on concrete structures, damage detection, and modeling techniques. Recent publications highlight advancements in predictive modeling for carbonation depth, crack growth, and thermal stress estimation, utilizing innovative technologies such as UAV and deep learning algorithms.

Articles (17)

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Year:

2020

Year:

2020

Collaborators (1)

Jong-Jae Lee

Assistant, Associate Professor

Sejong University

SOUTH KOREA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Yun-Kyu An

Research Interests

Explore related searches

Contact this professor

About

Articles (17)

Carbonation depth prediction of concrete bridges based on long short-term memory

Crack growth prediction on a concrete structure using deep ConvLSTM

Deep learning-based 3D digital damage map of vertical-type tunnels using unmanned fusion data scanning

Loop closure-based high-resolution façade digital modeling technique of large-scale dams using UAV

Thermal stress estimation of a constrained metallic plate using symmetric and antisymmetric Lamb wave group velocities

Computer vision-based statistical crack quantification for concrete structures

Leveraging the Characteristics of Ultrasonic Waves to Estimate Neutral Temperature of Continuous Welded Rails

Automated bridge crack evaluation through deep super resolution network-based hybrid image matching

Infrastructure BIM Platform for Lifecycle Management

Deep super resolution crack network (SrcNet) for improving computer vision–based automated crack detectability in in situ bridges

Deep Learning-Based Automated Background Removal for Structural Exterior Image Stitching

A novel 3D GPR image arrangement for deep learning-based underground object classification

Automated crack evaluation of a high-rise bridge pier using a ring-type climbing robot

Frequency–Wavenumber Analysis of Deep Learning-based Super Resolution 3D GPR Images

Probability-Based Concrete Carbonation Prediction Using On-Site Data

Remote Inspection of Internal Delamination in Wind Turbine Blades using Continuous Line Laser Scanning Thermography

Adaptive Subset-Based Digital Image Correlation for Fatigue Crack Evaluation

Collaborators (1)

Jong-Jae Lee

Make your next move.