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Tzu-Hsuan Lin ORCID

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Putranto, Alan / Huang, Bo-Xun / Lin, Tzu-Hsuan (2019): Electromagnetic wave-driven deep learning for structural evaluation of reinforced concrete strength. In: Journal of Civil Engineering and Management, v. 0, n. 0 (22 August 2019).

    https://doi.org/10.3846/jcem.2024.22266

  2. Putranto, Alan / Lin, Tzu-Hsuan / Huang, Bo-Xun (2024): Deep learning-integrated electromagnetic imaging for evaluating reinforced concrete structures in water-contact scenarios. In: Automation in Construction, v. 164 (August 2024).

    https://doi.org/10.1016/j.autcon.2024.105459

  3. Lin, Tzu-Hsuan / Chiang, Pin-Chian / Putranto, Alan (2024): Multispecies hybrid bioinspired climbing robot for wall tile inspection. In: Automation in Construction, v. 164 (August 2024).

    https://doi.org/10.1016/j.autcon.2024.105446

  4. Lin, Tzu-Hsuan / Chang, Chien-Ta / Yang, Bo-Hong / Hung, Chung-Chan / Wen, Kuo-Wei (2023): AI-powered shotcrete robot for enhancing structural integrity using ultra-high performance concrete and visual recognition. In: Automation in Construction, v. 155 (November 2023).

    https://doi.org/10.1016/j.autcon.2023.105038

  5. Lin, Tzu-Hsuan / Putranto, Alan / Chen, Pin-Hang / Teng, Yun-Zhen / Chen, Li (2023): High-mobility inchworm climbing robot for steel bridge inspection. In: Automation in Construction, v. 152 (August 2023).

    https://doi.org/10.1016/j.autcon.2023.104905

  6. Lin, Tzu-Hsuan / Huang, Yu-Hua / Putranto, Alan (2022): Intelligent question and answer system for building information modeling and artificial intelligence of things based on the bidirectional encoder representations from transformers model. In: Automation in Construction, v. 142 (Oktober 2022).

    https://doi.org/10.1016/j.autcon.2022.104483

  7. Lin, Tzu-Hsuan / Putranto, Alan / Wang, Yan-ting (2021): Smart sensor tags for seepage sensing protected by 3D-printed case for embedding in concrete structures. In: Construction and Building Materials, v. 284 (Mai 2021).

    https://doi.org/10.1016/j.conbuildmat.2021.122784

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