3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CV2026
Searching for Robust Augmentations to Improve Out-of-Domain Generalization in Dermoscopic Skin Cancer Classification
Alexander Kozachok, Ilya Latyshev, Evgeny Karpulevich +3
Background/Objectives: Dermoscopic skin-lesion classifiers lose accuracy when images arrive from a new clinic or a new device. We asked which data augmentations reduce that loss, a…
eess.IV2024★ 3 cited
MamT: Multi-view Attention Networks for Mammography Cancer Classification
Alisher Ibragimov, Sofya Senotrusova, Arsenii Litvinov +3
In this study, we introduce a novel method, called MamT, which is used for simultaneous analysis of four mammography images. A decision is made based on one image of a breast,…