Deep neural networks are trained to recover low-order Fourier elliptical components describing overall shape and orientation from simulated transit light curves of arbitrary 2D objects.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Derives pole at (276.79°, -21.43°), 28.4517 min period, S-type classification, ~27.4 m size, and thermal inertia 163 J m^{-2} K^{-1} s^{-1/2} for Kamo'oalewa from light curves and a fitted Yarkovsky A2 value.
citing papers explorer
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Beyond Spherical geometry: Unraveling complex features of objects orbiting around stars from its transit light curve using deep learning
Deep neural networks are trained to recover low-order Fourier elliptical components describing overall shape and orientation from simulated transit light curves of arbitrary 2D objects.
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Physical Characteristics of the Asteroid (469219) Kamo'oalewa as a target of the Chinese Tianwen-2 mission
Derives pole at (276.79°, -21.43°), 28.4517 min period, S-type classification, ~27.4 m size, and thermal inertia 163 J m^{-2} K^{-1} s^{-1/2} for Kamo'oalewa from light curves and a fitted Yarkovsky A2 value.