Hyunjun Kim 
- (2023): Framework for rapid characterization of fresh properties of cementitious materials using point cloud and machine learning. Dans: Construction and Building Materials, v. 400 (octobre 2023).
- (2024): Evaluation of aggregate segregation in self-consolidating concrete using 3D point cloud analysis. Dans: Journal of Building Engineering, v. 82 (avril 2024).
- (2017): Comparative analysis of image binarization methods for crack identification in concrete structures. Dans: Cement and Concrete Research, v. 99 (septembre 2017).
- (2021): Framework for characterizing the time-dependent volumetric properties of aerated cementitious material. Dans: Construction and Building Materials, v. 284 (mai 2021).
- (2023): Automated bridge component recognition using close-range images from unmanned aerial vehicles. Dans: Engineering Structures, v. 274 (janvier 2023).
- (2022): Nontarget-based displacement measurement using LiDAR and camera. Dans: Automation in Construction, v. 142 (octobre 2022).
- (2016): A new methodology development for flood fragility curve derivation considering structural deterioration for bridges. Dans: Smart Structures and Systems, v. 17, n. 1 (janvier 2016).
- (2015): Experimental validation of Kalman filter-based strain estimation in structures subjected to non-zero mean input. Dans: Smart Structures and Systems, v. 15, n. 2 (février 2015).
- (2022): Automated concrete crack evaluation using stereo vision with two different focal lengths. Dans: Automation in Construction, v. 135 (mars 2022).
- (2021): Long-term autogenous healing and re-healing performance in concrete: Evaluation using air-coupled surface-wave method. Dans: Construction and Building Materials, v. 307 (novembre 2021).
- (2021): Automated Damage Localization and Quantification in Concrete Bridges Using Point Cloud-Based Surface-Fitting Strategy. Dans: Journal of Computing in Civil Engineering, v. 35, n. 6 (novembre 2021).
- (2022): Monitoring of self-healing in concrete with micro-capsules using a combination of air-coupled surface wave and computer-vision techniques. Dans: Structural Health Monitoring, v. 21, n. 4 (janvier 2022).
- (2020): Crack identification method for concrete structures considering angle of view using RGB-D camera-based sensor fusion. Dans: Structural Health Monitoring, v. 20, n. 2 (octobre 2020).
- (2021): Automated wireless monitoring system for cable tension forces using deep learning. Dans: Structural Health Monitoring, v. 20, n. 4 (avril 2021).
- (2018): Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning. Dans: Structural Health Monitoring, v. 18, n. 3 (mars 2018).
- (2020): Rheology-based determination of injectable grout fluidity for preplaced aggregate concrete using ultrasonic tomography. Dans: Construction and Building Materials, v. 260 (novembre 2020).
- (2020): Automated bridge component recognition from point clouds using deep learning. Dans: Structural Control and Health Monitoring, v. 27, n. 9 (juin 2020).
- (2020): Microstructural characteristics of sound absorbable porous cement-based materials by incorporating natural fibers and aluminum powder. Dans: Construction and Building Materials, v. 243 (mai 2020).
- (2019): Automated peak picking using region‐based convolutional neural network for operational modal analysis. Dans: Structural Control and Health Monitoring, v. 26, n. 11 (septembre 2019).
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