Classifying galaxy mergers with JWST/HST and CNNs
This entry explores how to classify merging galaxies vs. non-merging galaxies from multi-wavelength imaging from the James Webb Space Telescope (JWST) and the Hubble Space Telescope (HST) with convolutional neural networks (CNNs). This approach was used by the DeepMerge team (Ciprijanovic et al. 2020) to classify mergers in sythetic observations of simulated galaxies. The same workflow is presented in simplifed format to walk through the construction of the CNN model. The results are then validated and the performance is discussed.
Data: The DeepMerge HLSP
Notebook: Classifying JWST-HST galaxy mergers with CNNs
Tags: classification, deep learning, 1d data