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Found 3 papers, 2 papers with code
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation -- Analysis of Ranking Metrics and Benchmarking Results
In this study, we explore and evaluate a metric developed during the BraTS 2019-2020 task on uncertainty quantification (QU-BraTS), and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation.
MANTRA: A Machine Learning reference lightcurve dataset for astronomical transient event recognition
It achieves an F1-score of 96. 25% in the binary classification and 52. 79% in the eight-class classification.
Classifying Image Sequences of Astronomical Transients with Deep Neural Networks
Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts.
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