Can deep models benefit from standard preprocessing of pulsed thermography data? (2022)
- Authors:
- Autor USP: TARPANI, JOSÉ RICARDO - EESC
- Unidade: EESC
- DOI: 10.1109/IRMMW-THz50927.2022.9896112
- Subjects: TERMOGRAFIA; APRENDIZADO COMPUTACIONAL; MATERIAIS
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway, NJ, USA
- Date published: 2022
- Conference titles: International Conference on Infrared, Millimeter and Terahertz Waves - IRMMW-THz
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
WEI, Z. et al. Can deep models benefit from standard preprocessing of pulsed thermography data? 2022, Anais.. Piscataway, NJ, USA: IEEE, 2022. Disponível em: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112. Acesso em: 23 jan. 2026. -
APA
Wei, Z., Osman, A., Muller, D., Fernandes, H., Tarpani, J. R., & Maldague, X. (2022). Can deep models benefit from standard preprocessing of pulsed thermography data? In . Piscataway, NJ, USA: IEEE. doi:10.1109/IRMMW-THz50927.2022.9896112 -
NLM
Wei Z, Osman A, Muller D, Fernandes H, Tarpani JR, Maldague X. Can deep models benefit from standard preprocessing of pulsed thermography data? [Internet]. 2022 ;[citado 2026 jan. 23 ] Available from: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112 -
Vancouver
Wei Z, Osman A, Muller D, Fernandes H, Tarpani JR, Maldague X. Can deep models benefit from standard preprocessing of pulsed thermography data? [Internet]. 2022 ;[citado 2026 jan. 23 ] Available from: https://doi.org/10.1109/IRMMW-THz50927.2022.9896112 - Impact performance of egg-box core sandwich panels made from sisal fibers and castor-oil-based polymer
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Informações sobre o DOI: 10.1109/IRMMW-THz50927.2022.9896112 (Fonte: oaDOI API)
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