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3 Pith papers cite this work. Polarity classification is still indexing.

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Single object observations: Large telescopes vs. multiple small telescopes

astro-ph.IM · 2026-06-25 · unverdicted · novelty 5.0

Modeling indicates arrays of small seeing-limited telescopes are more cost-effective than single large seeing-limited ones for single-object observations, with single diffraction-limited telescopes preferred only below 20-28 magnitudes depending on architecture.

Streak detection in the VST/OmegaCAM archive using deep learning

astro-ph.IM · 2026-06-29 · unverdicted · novelty 4.0

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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Showing 2 of 2 citing papers after filters.

  • Single object observations: Large telescopes vs. multiple small telescopes astro-ph.IM · 2026-06-25 · unverdicted · none · ref 11

    Modeling indicates arrays of small seeing-limited telescopes are more cost-effective than single large seeing-limited ones for single-object observations, with single diffraction-limited telescopes preferred only below 20-28 magnitudes depending on architecture.

  • Streak detection in the VST/OmegaCAM archive using deep learning astro-ph.IM · 2026-06-29 · unverdicted · none · ref 190

    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