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How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events
We present a case study of solar flare forecasting by means of metadata feature time series, by treating it as a prominent class-imbalance and temporally coherent problem.
Toward Filament Segmentation Using Deep Neural Networks
Despite the known challenges in the identification and characterization of filaments by the existing module, which in turn are inherited into any other module that intends to learn from such outputs, Mask R-CNN shows promising results.
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data
This is in particular prevalent in interdisciplinary research where the theoretical aspects are sometimes overshadowed by the challenges of the application.
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