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Angelo Cardellicchio ORCID

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. Cardellicchio, Angelo / Ruggieri, Sergio / Nettis, Andrea / Renò, Vito / Uva, Giuseppina (2023): Physical interpretation of machine learning-based recognition of defects for the risk management of existing bridge heritage. In: Engineering Failure Analysis, v. 149 (July 2023).

    https://doi.org/10.1016/j.engfailanal.2023.107237

  2. Ruggieri, Sergio / Cardellicchio, Angelo / Nettis, Andrea / Renò, Vito / Uva, Giuseppina (2023): Using machine learning approaches to perform defect detection of existing bridges. In: Procedia Structural Integrity, v. 44 ( 2023).

    https://doi.org/10.1016/j.prostr.2023.01.259

  3. Ruggieri, Sergio / Cardellicchio, Angelo / Uva, Giuseppina (2023): Using transfer learning technique to define seismic vulnerability of existing buildings through mechanical models. In: Procedia Structural Integrity, v. 44 ( 2023).

    https://doi.org/10.1016/j.prostr.2023.01.251

  4. Cardellicchio, Angelo / Ruggieri, Sergio / Leggieri, Valeria / Uva, Giuseppina (2023): A machine learning framework to estimate a simple seismic vulnerability index from a photograph: the VULMA project. In: Procedia Structural Integrity, v. 44 ( 2023).

    https://doi.org/10.1016/j.prostr.2023.01.250

  5. Ruggieri, Sergio / Calò, Mirko / Cardellicchio, Angelo / Uva, Giuseppina (2022): Analytical-mechanical based framework for seismic overall fragility analysis of existing RC buildings in town compartments. In: Bulletin of Earthquake Engineering, v. 20, n. 15 (6 October 2022).

    https://doi.org/10.1007/s10518-022-01516-7

  6. Ruggieri, Sergio / Cardellicchio, Angelo / Leggieri, Valeria / Uva, Giuseppina (2021): Machine-learning based vulnerability analysis of existing buildings. In: Automation in Construction, v. 132 (December 2021).

    https://doi.org/10.1016/j.autcon.2021.103936

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