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References from Metric discordance under MIDOG++ domain shift: a leave-one-domain-out audit of F1, emitted-detection confidence calibration, and ROI count error. Local targets link to admitted publications; unresolved targets remain external evidence.
A comprehensive multi-domain dataset for mitotic figure detection
10.1038/s41597-023-02327-4 · 2023 · External reference
Domain generalization across tumor types, laboratories, and species: insights from the 2022 edition of the Mitosis Domain Generalization Challenge
10.1016/j.media.2024.103155 · 2024 · External reference
Mitosis domain generalization in histopathology images: the MIDOG challenge
10.1016/j.media.2022.102699 · 2023 · External reference
On calibration of modern neural networks
2017 · External reference
Multivariate confidence calibration for object detection
2020 · External reference
Confidence calibration for object detection and segmentation
2022 · External reference
Algorithmic fairness in artificial intelligence for medicine and healthcare
10.1038/s41551-023-01056-8 · 2023 · External reference
Distributionally robust neural networks for group shifts: on the importance of regularization for worst-case generalization
2020 · External reference
Domain-adversarial training of neural networks
2016 · External reference
Domain generalization in computational pathology: survey and guidelines
10.1145/3724391 · 2025 · External reference
Measuring calibration in deep learning
2019 · External reference
Obtaining well calibrated probabilities using Bayesian binning
2015 · External reference
Focal loss for dense object detection
2017 · External reference
