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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Multi-technique observations constrain the configuration of the ξ Tau system, detecting orbital oscillations on multiple timescales and suggesting component C is itself a binary.
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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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Configuration of the $\xi$ Tau system constrained by multi-technique observations
Multi-technique observations constrain the configuration of the ξ Tau system, detecting orbital oscillations on multiple timescales and suggesting component C is itself a binary.
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