Peláez-Rodriguez, C.; Iglesias-Pordomingo, Á.; Salcedo-Sanz, S.; Lorenzana, A.; Magdaleno, A.
Structural Damage Detection Using Adversarially Calibrated Simulations and Deep Learning from Frequency-Domain Signals. Appl. Sci. 2025, 15, 12731.
https://doi.org/10.3390/app152312731
AMA Style
Peláez-Rodriguez C, Iglesias-Pordomingo Á, Salcedo-Sanz S, Lorenzana A, Magdaleno A.
Structural Damage Detection Using Adversarially Calibrated Simulations and Deep Learning from Frequency-Domain Signals. Applied Sciences. 2025; 15(23):12731.
https://doi.org/10.3390/app152312731
Chicago/Turabian Style
Peláez-Rodriguez, César, Álvaro Iglesias-Pordomingo, Sancho Salcedo-Sanz, Antolin Lorenzana, and Alvaro Magdaleno.
2025. "Structural Damage Detection Using Adversarially Calibrated Simulations and Deep Learning from Frequency-Domain Signals" Applied Sciences 15, no. 23: 12731.
https://doi.org/10.3390/app152312731
APA Style
Peláez-Rodriguez, C., Iglesias-Pordomingo, Á., Salcedo-Sanz, S., Lorenzana, A., & Magdaleno, A.
(2025). Structural Damage Detection Using Adversarially Calibrated Simulations and Deep Learning from Frequency-Domain Signals. Applied Sciences, 15(23), 12731.
https://doi.org/10.3390/app152312731