APA (7th ed.) Citation

Choi, Y., Lee, T., Yeom, Y., Kwon, S., Kim, H., Lee, K., . . . Song, S. (2023). Development of Maximum Residual Stress Prediction Technique for Shot-Peened Specimen Using Rayleigh Wave Dispersion Data Based on Convolutional Neural Network. Materials (1996-1944), 16(23), 7406. https://doi.org/10.3390/ma16237406

Chicago Style (17th ed.) Citation

Choi, Yeong-Won, Taek-Gyu Lee, Yun-Taek Yeom, Sung-Duk Kwon, Hun-Hee Kim, Kee-Young Lee, Hak-Joon Kim, and Sung-Jin Song. "Development of Maximum Residual Stress Prediction Technique for Shot-Peened Specimen Using Rayleigh Wave Dispersion Data Based on Convolutional Neural Network." Materials (1996-1944) 16, no. 23 (2023): 7406. https://doi.org/10.3390/ma16237406.

MLA (9th ed.) Citation

Choi, Yeong-Won, et al. "Development of Maximum Residual Stress Prediction Technique for Shot-Peened Specimen Using Rayleigh Wave Dispersion Data Based on Convolutional Neural Network." Materials (1996-1944), vol. 16, no. 23, 2023, p. 7406, https://doi.org/10.3390/ma16237406.