Seungbo Shim 
- (2023): Self‐training approach for crack detection using synthesized crack images based on conditional generative adversarial network. In: Computer-Aided Civil and Infrastructure Engineering, v. 39, n. 7 (November 2023).
- (2023): Learning Structure for Concrete Crack Detection Using Robust Super-Resolution with Generative Adversarial Network. In: Structural Control and Health Monitoring, v. 2023 (Februar 2023).
- (2023): Remote robotic system for 3D measurement of concrete damage in tunnel with ground vehicle and manipulator. In: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 15 (April 2023).
- (2022): Stereo-vision-based 3D concrete crack detection using adversarial learning with balanced ensemble discriminator networks. In: Structural Health Monitoring, v. 22, n. 2 (Mai 2022).
- (2022): Efficiency Analysis of Filter-Based Calibration Technique to Improve Tunnel Measurement Reliability. In: KSCE Journal of Civil Engineering, v. 26, n. 6 (April 2022).
- (2022): Road damage detection using super-resolution and semi-supervised learning with generative adversarial network. In: Automation in Construction, v. 135 (März 2022).
- (2021): Road surface damage detection based on hierarchical architecture using lightweight auto-encoder network. In: Automation in Construction, v. 130 (Oktober 2021).
- (2021): Lightweight pixel-wise segmentation for efficient concrete crack detection using hierarchical convolutional neural network. In: Smart Materials and Structures, v. 30, n. 4 (Februar 2021).
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