Transfer learning for galaxy morphology from one survey to another

Understand

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications.

• However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them).
• A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e.
• if the features learned by the machines are meaningful for different data.