Duran-Lopez, L.; Dominguez-Morales, J.P.; Rios-Navarro, A.; Gutierrez-Galan, D.; Jimenez-Fernandez, A.; Vicente-Diaz, S.; Linares-Barranco, A.
Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed. Sensors 2021, 21, 1122.
https://doi.org/10.3390/s21041122
AMA Style
Duran-Lopez L, Dominguez-Morales JP, Rios-Navarro A, Gutierrez-Galan D, Jimenez-Fernandez A, Vicente-Diaz S, Linares-Barranco A.
Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed. Sensors. 2021; 21(4):1122.
https://doi.org/10.3390/s21041122
Chicago/Turabian Style
Duran-Lopez, Lourdes, Juan P. Dominguez-Morales, Antonio Rios-Navarro, Daniel Gutierrez-Galan, Angel Jimenez-Fernandez, Saturnino Vicente-Diaz, and Alejandro Linares-Barranco.
2021. "Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed" Sensors 21, no. 4: 1122.
https://doi.org/10.3390/s21041122
APA Style
Duran-Lopez, L., Dominguez-Morales, J. P., Rios-Navarro, A., Gutierrez-Galan, D., Jimenez-Fernandez, A., Vicente-Diaz, S., & Linares-Barranco, A.
(2021). Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed. Sensors, 21(4), 1122.
https://doi.org/10.3390/s21041122
