Adversarial training applied to Convolutional Neural Network for photometric redshift predictions

24 Feb 2020 Campagne Jean-Eric

The use of Convolutional Neural Networks (CNN) to estimate the galaxy photometric redshift probability distribution by analysing the images in different wavelength bands has been developed in the recent years thanks to the rapid development of the Machine Learning (ML) ecosystem. Authors have set-up CNN architectures and studied their performances and some sources of systematics using standard methods of training and testing to ensure the generalisation power of their models... (read more)

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  • INSTRUMENTATION AND METHODS FOR ASTROPHYSICS
  • IMAGE AND VIDEO PROCESSING