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Alessandro Sabato ORCID

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

  1. Kulkarni, Nitin Nagesh / Sabato, Alessandro: Full-field expansion and damage detection from sparse measurements using physics-informed variational autoencoders. In: Structural Health Monitoring.

    https://doi.org/10.1177/14759217241289575

  2. Dabetwar, Shweta / Padhye, Richa / Kulkarni, Nitin Nagesh / Niezrecki, Christopher / Sabato, Alessandro (2023): Performance evaluation of deep learning algorithms for heat loss damage classification in buildings from UAV-borne infrared images. In: Journal of Building Engineering, v. 75 (September 2023).

    https://doi.org/10.1016/j.jobe.2023.106948

  3. Kulkarni, Nitin Nagesh / Raisi, Koosha / Valente, Nicholas A. / Benoit, Jason / Yu, Tzuyang / Sabato, Alessandro (2023): Deep learning augmented infrared thermography for unmanned aerial vehicles structural health monitoring of roadways. In: Automation in Construction, v. 148 (April 2023).

    https://doi.org/10.1016/j.autcon.2023.104784

  4. Dabetwar, Shweta / Kulkarni, Nitin Nagesh / Angelosanti, Marco / Niezrecki, Christopher / Sabato, Alessandro (2022): Sensitivity analysis of unmanned aerial vehicle-borne 3D point cloud reconstruction from infrared images. In: Journal of Building Engineering, v. 58 (Oktober 2022).

    https://doi.org/10.1016/j.jobe.2022.105070

  5. Puliti, Marco / Montaggioli, Giovanni / Sabato, Alessandro (2021): Automated subsurface defects' detection using point cloud reconstruction from infrared images. In: Automation in Construction, v. 129 (September 2021).

    https://doi.org/10.1016/j.autcon.2021.103829

  6. Reagan, Daniel / Sabato, Alessandro / Niezrecki, Christopher (2017): Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges. In: Structural Health Monitoring, v. 17, n. 5 (Oktober 2017).

    https://doi.org/10.1177/1475921717735326

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