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Papers, like this one from Google, show that Deep Learning and Machine Learning are effective in detecting exoplanets from luminosity data provided by telescopes like TESS or Kepler.

These models seem extremely quick and lightweight. Has it become somewhat of a standard practice to use these on freshly obtained TESS data? If not, why, and what is done with the data instead? Are there drawbacks to using these seemingly accurate models?

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closed as off-topic by GdD, JCRM, Jan Doggen, Fred, DrSheldon May 30 at 13:28

This question appears to be off-topic. The users who voted to close gave this specific reason:

  • "This question is about other space sciences (physics, weather, astronomy, etc), and does not directly pertain to space exploration as outlined in the help center." – GdD, JCRM, Jan Doggen, Fred, DrSheldon
If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ I think this question might receive good answers in Astronomy SE also. If you don't have much luck here I'd recommend moving it. $\endgroup$ – uhoh May 30 at 7:38
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    $\begingroup$ @uhoh I guess I'll do that. I had no idea that it existed. If I'm not mistaken, there was an old Astronomy SE from Area 51 that ended up being merged with Physics SE. Never knew someone restarted it. $\endgroup$ – Aditya Radhakrishnan May 30 at 7:56
  • $\begingroup$ Wow, you are a Stack Exchange historian, there should be a badge for that! There are almost 200 SE sites now. $\endgroup$ – uhoh May 30 at 8:15
  • $\begingroup$ Since this question is about data analysis of space telescopes like TESS, it certainly is on-topic. However, now that it is posted in Astronomy it is best for your to delete it here. "cross-posting" of the same or similar questions on more than one site at the same time is strongly discouraged. $\endgroup$ – uhoh May 30 at 10:25