no code implementations • 2 Nov 2023 • Deval Mehta, Brigid Betz-Stablein, Toan D Nguyen, Yaniv Gal, Adrian Bowling, Martin Haskett, Maithili Sashindranath, Paul Bonnington, Victoria Mar, H Peter Soyer, ZongYuan Ge
For a clinical image, our model generates three outputs: a hierarchical prediction, an alert for out-of-distribution images, and a recommendation for dermoscopy if clinical image alone is insufficient for diagnosis.
no code implementations • 13 Sep 2022 • Zhen Yu, Toan Nguyen, Yaniv Gal, Lie Ju, Shekhar S. Chandra, Lei Zhang, Paul Bonnington, Victoria Mar, Zhiyong Wang, ZongYuan Ge
Accordingly, the learned prototypes preserve the semantic class relations in the embedding space and we can predict the label of an image by assigning its feature to the nearest hyperbolic class prototype.
1 code implementation • 30 Jun 2022 • Deval Mehta, Yaniv Gal, Adrian Bowling, Paul Bonnington, ZongYuan Ge
Through this approach, 1) First, we target the mixup amongst middle and tail classes to address the long-tail problem.