4 papers
Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification
Raphaël Bonnet-Guerrini, Bruno Sanchez, Dominique Fouchez +5
Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable labels are costly, while communi…
New substellar candidates identified through deep learning in the F150 sample of the large-scale SHINE direct imaging survey
Carles Cantero Mitjans, Mariam Sabalbal, Olivier Absil +3
Context. The SPHERE High-contrast Imaging survey for Exoplanets (SHINE) represents one of the largest direct imaging campaigns, targeting over 400 young, nearby stars with the goal…
Enhanced detection limits in the SHINE F150 survey through the Regime Switching Model. Optimizing thresholds and investigating environmental noise
Mariam Sabalbal, Olivier Absil, Carl-Henrik Dahlqvist +1
In high-contrast imaging, a novel detection algorithm for angular differential imaging (ADI) sequences has recently been introduced: the Regime Switching Model (RSM). In this study…
Exoplanet Imaging Data Challenge, phase II: Comparison of algorithms in terms of characterization capabilities
Faustine Cantalloube, Valentin Christiaens, Carles Cantero Mitjans +15
In this communication, we report on the results of the second phase of the Exoplanet Imaging Data Challenge started in 2019. This second phase focuses on the characterization of po…