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Found 4 papers, 1 papers with code
CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations
In recent years, several unsupervised cell segmentation methods have been presented, trying to omit the requirement of laborious pixel-level annotations for the training of a cell segmentation model.
Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design
The field of antibody-based therapeutics has grown significantly in recent years, with targeted antibodies emerging as a potentially effective approach to personalized therapies.
Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles
In this work, we put the focus back on tumor localization in form of a patch-level classification task and take up the setting of so-called coarse annotations, which provide greater training supervision while remaining feasible from a clinical standpoint.
Probing Contextual Diversity for Dense Out-of-Distribution Detection
Detection of out-of-distribution (OoD) samples in the context of image classification has recently become an area of interest and active study, along with the topic of uncertainty estimation, to which it is closely related.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
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