7 citations · 12 across the 3 of their papers we have counts for
3 papers
eess.IV2024★ 7 cited
Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging
Daniela L. Ramos, Hector J. Hortua
Colorectal polyps are generally benign alterations that, if not identified promptly and managed successfully, can progress to cancer and cause affectations on the colon mucosa, kno…
cs.LG2022★ 1 cited
Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks
Sergio A. Balanya, Juan Maroñas, Daniel Ramos
In this paper, we study the post-hoc calibration of modern neural networks, a problem that has drawn a lot of attention in recent years. Many calibration methods of varying complex…
cs.LG2020★ 4 cited
On Calibration of Mixup Training for Deep Neural Networks
Juan Maroñas, Daniel Ramos, Roberto Paredes
Deep Neural Networks (DNN) represent the state of the art in many tasks. However, due to their overparameterization, their generalization capabilities are in doubt and still a fiel…