A W-Net deep learning model detects asteroids in TESS data independently of trajectory by rotating training image cubes and using adaptive normalization for data scaling.
Revista Mexicana de Astronomia y Astrofisica Conference Series , year = 2007, editor =
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3representative citing papers
Three accelerating stars yield one stellar companion at 166 AU, one 45 Jupiter-mass object at ~18 AU, and one 9.5 Jupiter-mass object at 6.4 AU that is 65% likely to be a planet.
A uniform spectroscopic catalog of 625 exoplanet hosts shows subsolar-metallicity giant-planet hosts are alpha-enhanced relative to both iron-rich hosts and typical metal-poor field stars.
citing papers explorer
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Trajectory-Agnostic Asteroid Detection in TESS with Deep Learning
A W-Net deep learning model detects asteroids in TESS data independently of trajectory by rotating training image cubes and using adaptive normalization for data scaling.
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Gaia Exoplanet Orbits, Demographics, and Evolution Survey (GEODES): Characteristics of Three Long-Period Companions Accelerating their Host Stars
Three accelerating stars yield one stellar companion at 166 AU, one 45 Jupiter-mass object at ~18 AU, and one 9.5 Jupiter-mass object at 6.4 AU that is 65% likely to be a planet.
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A Uniform Determination of the Bulk Metallicities and Alpha Enrichments of Confirmed Exoplanet Systems with TRES
A uniform spectroscopic catalog of 625 exoplanet hosts shows subsolar-metallicity giant-planet hosts are alpha-enhanced relative to both iron-rich hosts and typical metal-poor field stars.