888 citations · 4.1k across the 38 of their papers we have counts for
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astro-ph.IM2022
Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods
Q. Lin, D. Fouchez, J. Pasquet +4
Deep Learning models have been increasingly exploited in astrophysical studies, yet such data-driven algorithms are prone to producing biased outputs detrimental for subsequent ana…
astro-ph.IM2018★ 190 cited
Photometric redshifts from SDSS images using a Convolutional Neural Network
Johanna Pasquet, Emmanuel Bertin, Marie Treyer +2
We developed a Deep Convolutional Neural Network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies…