Source: Procedia CIRP. Conference titles: CIRP Conference on Intelligent Computation in Manufacturing Engineering. Unidade: EESC
Subjects: MATERIAIS COMPÓSITOS, VISÃO COMPUTACIONAL, REDES NEURAIS
ABNT
MONSON, Paulo Monteiro de Carvalho et al. Computer vision-based deep learning approach for automated delamination detection and classification in carbon fiber-reinforced polymer composites. Procedia CIRP. Amsterdam, Netherlands: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: http://dx.doi.org/10.1016/j.procir.2026.01.176. Acesso em: 19 abr. 2026. , 2026APA
Monson, P. M. de C., Conceição Junior, P. de O., Rodrigues, A. R., & Dotto, F. R. L. (2026). Computer vision-based deep learning approach for automated delamination detection and classification in carbon fiber-reinforced polymer composites. Procedia CIRP. Amsterdam, Netherlands: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1016/j.procir.2026.01.176NLM
Monson PM de C, Conceição Junior P de O, Rodrigues AR, Dotto FRL. Computer vision-based deep learning approach for automated delamination detection and classification in carbon fiber-reinforced polymer composites [Internet]. Procedia CIRP. 2026 ; 138 1021-1024.[citado 2026 abr. 19 ] Available from: http://dx.doi.org/10.1016/j.procir.2026.01.176Vancouver
Monson PM de C, Conceição Junior P de O, Rodrigues AR, Dotto FRL. Computer vision-based deep learning approach for automated delamination detection and classification in carbon fiber-reinforced polymer composites [Internet]. Procedia CIRP. 2026 ; 138 1021-1024.[citado 2026 abr. 19 ] Available from: http://dx.doi.org/10.1016/j.procir.2026.01.176
