APA (7th ed.) Citation

Woldesellasse, H., & Tesfamariam, S. (2023). Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network. Journal of Pipeline Science and Engineering, 3(1), 100091. https://doi.org/10.1016/j.jpse.2022.100091

Chicago Style (17th ed.) Citation

Woldesellasse, Haile, and Solomon Tesfamariam. "Data Augmentation Using Conditional Generative Adversarial Network (cGAN): Application for Prediction of Corrosion Pit Depth and Testing Using Neural Network." Journal of Pipeline Science and Engineering 3, no. 1 (2023): 100091. https://doi.org/10.1016/j.jpse.2022.100091.

MLA (9th ed.) Citation

Woldesellasse, Haile, and Solomon Tesfamariam. "Data Augmentation Using Conditional Generative Adversarial Network (cGAN): Application for Prediction of Corrosion Pit Depth and Testing Using Neural Network." Journal of Pipeline Science and Engineering, vol. 3, no. 1, 2023, p. 100091, https://doi.org/10.1016/j.jpse.2022.100091.