APA (7th ed.) Citation

Garbin, C., Zhu, X., & Marques, O. (2020). Dropout vs. batch normalization: An empirical study of their impact to deep learning. Multimedia tools and applications, 79(19-20), 12777-12815. https://doi.org/10.1007/s11042-019-08453-9

Chicago Style (17th ed.) Citation

Garbin, Christian, Xingquan Zhu, and Oge Marques. "Dropout Vs. Batch Normalization: An Empirical Study of Their Impact to Deep Learning." Multimedia Tools and Applications 79, no. 19-20 (2020): 12777-12815. https://doi.org/10.1007/s11042-019-08453-9.

MLA (9th ed.) Citation

Garbin, Christian, et al. "Dropout Vs. Batch Normalization: An Empirical Study of Their Impact to Deep Learning." Multimedia Tools and Applications, vol. 79, no. 19-20, 2020, pp. 12777-12815, https://doi.org/10.1007/s11042-019-08453-9.