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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3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Spectral disentangling of ET Cru yields masses of 13.41 and 6.00 solar masses with 1.3% precision and shows the secondary has severe CNO-cycle chemical anomalies exceeding typical Algol systems.
Model-independent masses and radii plus effective temperatures are derived for the F9 V primary (M1=1.36 Msun, R1=1.72 Rsun, Teff=6197 K) and M-dwarf secondary (M2=0.56 Msun, R2=0.53 Rsun, Teff=3770 K) in CD-27 2812.
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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Spectral Disentangling Reveals Deep CNO-cycle Exposure in ET Cru
Spectral disentangling of ET Cru yields masses of 13.41 and 6.00 solar masses with 1.3% precision and shows the secondary has severe CNO-cycle chemical anomalies exceeding typical Algol systems.
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Fundamental effective temperature measurements for eclipsing binary stars -- VIII. NIRPS spectroscopy of CD-27 2812
Model-independent masses and radii plus effective temperatures are derived for the F9 V primary (M1=1.36 Msun, R1=1.72 Rsun, Teff=6197 K) and M-dwarf secondary (M2=0.56 Msun, R2=0.53 Rsun, Teff=3770 K) in CD-27 2812.