A two-stage deep learning pipeline (HT-LCNN detector + VGG6 classifier) trained on augmented real and simulated data detects streaks in OmegaCAM frames with F1 > 0.95 on test sets and 0.99 precision on real 2023 data, uncovering 25,335 streaks including >20% uncatalogued objects across 1.2 million f
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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astro-ph.IM 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Reanalysis of INT GSO debris survey data with blind stacking and refined astrometry recovers 25 new tracklets, achieves sub-arcsecond accuracy, and extracts light curves showing higher variability in faint objects.
citing papers explorer
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Streak detection in the VST/OmegaCAM archive using deep learning
A two-stage deep learning pipeline (HT-LCNN detector + VGG6 classifier) trained on augmented real and simulated data detects streaks in OmegaCAM frames with F1 > 0.95 on test sets and 0.99 precision on real 2023 data, uncovering 25,335 streaks including >20% uncatalogued objects across 1.2 million f
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DebrisWatch II: Digging deeper for geosynchronous debris
Reanalysis of INT GSO debris survey data with blind stacking and refined astrometry recovers 25 new tracklets, achieves sub-arcsecond accuracy, and extracts light curves showing higher variability in faint objects.