Rotation-invariant convolutional neural networks for galaxy morphology prediction
Rotation-invariant convolutional neural networks for galaxy morphology prediction
Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey have resulted in the availability of very large collections of images, which have permitted population-wide analyses of galaxy morphology. Morphological analysis has traditionally been carried out …