Catalog-free modeling of galaxy types in deep images – massive dimensional reduction with neural networks

HIGHLIGHTS

• who: Livet F. et al. from the Institut d'Astrophysique Paris, Sorbonne Université, CNRS, UMR, bis boulevard Arago, Paris, France have published the research: Catalog-free modeling of galaxy types in deep images - Massive dimensional reduction with neural networks, in the Journal: (JOURNAL)
• what: Using synthetic photometric multiband deep fields similar to previously reported CFHTLS and WIRDS D1/D2 deep fields and massively compressing them through the convolutional neural network the authors demonstrate the robustness accuracy and consistency of this new catalog-free inference method. The authors implement this method for the first time in . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.