no code implementations • 10 Apr 2021 • Deval Mehta, Umar Asif, Tian Hao, Erhan Bilal, Stefan von Cavallar, Stefan Harrer, Jeffrey Rogers
For BRADY we find F1-scores of 0. 75 using our framework compared to 0. 50 for the video based rater clinicians, while for PIGD we find 0. 78 for the framework and 0. 45 for the video based rater clinicians.
no code implementations • 29 Jul 2019 • Erhan Bilal
As opposed to batch normalization (BN), INN has no learnable parameters however it matches its performance on CIFAR10 and ImageNet classification tasks.
no code implementations • 8 Mar 2017 • Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger
Consider a regression problem where there is no labeled data and the only observations are the predictions $f_i(x_j)$ of $m$ experts $f_{i}$ over many samples $x_j$.