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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Shim, Seungbo: Self‐training approach for crack detection using synthesized crack images based on conditional generative adversarial network. In: Computer-Aided Civil and Infrastructure Engineering.

    https://doi.org/10.1111/mice.13119

  2. Kim, Jin / Shim, Seungbo / Kang, Seok-Jun / Cho, Gye-Chun (2023): Learning Structure for Concrete Crack Detection Using Robust Super-Resolution with Generative Adversarial Network. In: Structural Control and Health Monitoring, v. 2023 (February 2023).

    https://doi.org/10.1155/2023/8850290

  3. Shim, Seungbo / Lee, Seong‐Won / Cho, Gye‐Chun / Kim, Jin / Kang, Sung‐Mo (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).

    https://doi.org/10.1111/mice.12982

  4. Shim, Seungbo / Kim, Jin / Cho, Gye-Chun / Lee, Seong-Won (2022): Stereo-vision-based 3D concrete crack detection using adversarial learning with balanced ensemble discriminator networks. In: Structural Health Monitoring, v. 22, n. 2 (May 2022).

    https://doi.org/10.1177/14759217221097868

  5. Choi, Sang-il / Shim, Seungbo / Kong, Suk-Min / Kim, Yeong Bae / Lee, Seong-Won (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).

    https://doi.org/10.1007/s12205-022-0891-x

  6. Shim, Seungbo / Kim, Jin / Lee, Seong-Won / Cho, Gye-Chun (2022): Road damage detection using super-resolution and semi-supervised learning with generative adversarial network. In: Automation in Construction, v. 135 (March 2022).

    https://doi.org/10.1016/j.autcon.2022.104139

  7. Shim, Seungbo / Kim, Jin / Lee, Seong-Won / Cho, Gye-Chun (2021): Road surface damage detection based on hierarchical architecture using lightweight auto-encoder network. In: Automation in Construction, v. 130 (October 2021).

    https://doi.org/10.1016/j.autcon.2021.103833

  8. Kim, Jin / Shim, Seungbo / Cha, Yohan / Cho, Gye-Chun (2021): Lightweight pixel-wise segmentation for efficient concrete crack detection using hierarchical convolutional neural network. In: Smart Materials and Structures, v. 30, n. 4 (February 2021).

    https://doi.org/10.1088/1361-665x/abea1e

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