Hyunjun Kim

Assistant Professor

Seoul National University

South Korea

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About

Hyunjun Kim is an Assistant Professor at Seoul National University of Science and Technology, South Korea. His research interests include automated mineral identification, structural condition assessment using 3D point clouds, and the evaluation of cementitious materials. His recent work focuses on the use of computer vision and machine learning techniques in structural health monitoring and characterization of concrete properties.

Articles (17)

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2024

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2024

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2024

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2024

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2024

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2023

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2022

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2022

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2021

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2021

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2021

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2021

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2020

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2020

Collaborators (6)

Seunghoo Jeong

Korea Railroad Research Institute

SOUTH KOREA

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Sukhoon Pyo

Assistant Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Myoungsu Shin

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Junhwa Lee

Assistant Professor

Pusan National University

SOUTH KOREA

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Sung-Han Sim

Professor

Sungkyunkwan University

SOUTH KOREA

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Jinyoung Yoon

Assistant Professor

Konkuk University

SOUTH KOREA

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Hyunjun Kim

Research Interests

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Articles (17)

Development of large-scale synthetic 3D point cloud datasets for vision-based bridge structural condition assessment

Evaluation of aggregate segregation in self-consolidating concrete using 3D point cloud analysis

Full-scale structural displacement measurement with camera ego-motion compensation using RGB and LiDAR cameras

Long-term displacement measurement system for bridge bearing capable of camera reposition

Random bridge generator as a platform for developing computer vision-based structural inspection algorithms

Automated Mineral Identification of Pozzolanic Materials Using XRD Patterns

Framework for rapid characterization of fresh properties of cementitious materials using point cloud and machine learning

Self-heating characteristics of electrically conductive cement composites with carbon black and carbon fiber

Automated bridge component recognition using close-range images from unmanned aerial vehicles

Monitoring of self-healing in concrete with micro-capsules using a combination of air-coupled surface wave and computer-vision techniques

Automated concrete crack evaluation using stereo vision with two different focal lengths

Automated Damage Localization and Quantification in Concrete Bridges Using Point Cloud-Based Surface-Fitting Strategy

Long-term autogenous healing and re-healing performance in concrete: Evaluation using air-coupled surface-wave method

Framework for characterizing the time-dependent volumetric properties of aerated cementitious material

Crack identification method for concrete structures considering angle of view using RGB-D camera-based sensor fusion

Automated wireless monitoring system for cable tension forces using deep learning

Rheology-based determination of injectable grout fluidity for preplaced aggregate concrete using ultrasonic tomography

Collaborators (6)

Seunghoo Jeong

Sukhoon Pyo

Myoungsu Shin

Junhwa Lee

Sung-Han Sim

Jinyoung Yoon

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