26 citations · 42 across the 6 of their papers we have counts for
4 papers · 1 filter
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
Tomáš Chobola, Yu Liu, Hanyi Zhang +2
Current deep learning-based low-light image enhancement methods often struggle with high-resolution images, and fail to meet the practical demands of visual perception across diver…
DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology
Valentin Koch, Sophia J. Wagner, Salome Kazeminia +5
In hematology, computational models offer significant potential to improve diagnostic accuracy, streamline workflows, and reduce the tedious work of analyzing single cells in perip…
B-Cos Aligned Transformers Learn Human-Interpretable Features
Manuel Tran, Amal Lahiani, Yashin Dicente Cid +7
Vision Transformers (ViTs) and Swin Transformers (Swin) are currently state-of-the-art in computational pathology. However, domain experts are still reluctant to use these models d…
Low-resource finetuning of foundation models beats state-of-the-art in histopathology
Benedikt Roth, Valentin Koch, Sophia J. Wagner +3
To handle the large scale of whole slide images in computational pathology, most approaches first tessellate the images into smaller patches, extract features from these patches, a…