31 citations · 34 across the 2 of their papers we have counts for
2 papers
eess.IV2024★ 3 cited
Characterizing the Interpretability of Attention Maps in Digital Pathology
Tomé Albuquerque, Anil Yüce, Markus D. Herrmann +1
Interpreting machine learning model decisions is crucial for high-risk applications like healthcare. In digital pathology, large whole slide images (WSIs) are decomposed into small…
eess.IV2022★ 31 cited
A comparative study between vision transformers and CNNs in digital pathology
Luca Deininger, Bernhard Stimpel, Anil Yuce +5
Recently, vision transformers were shown to be capable of outperforming convolutional neural networks when pretrained on sufficient amounts of data. In comparison to convolutional…