astro313

Machine learning and deep learning in astronomy:

Machine learning has a long history in astronomy, but deep learning (DL) only got traction since arount 2016. Here I will list current DL effords:

The main field of ML applications in astrophysics is object classification. With source counts now ranging into the 10⁷-10⁸ for most surveys, machine learning is put to use to allow the classification of a large number of sources which would otherwise need an infeasible amount of manpower:

• Classifying galaxies according to their HI content - SVM perform best in specisifity and is hence used over a DNN
• Morphological classification of radio galaxies: Capsule Networks versus Convolutional Neural Networks *05/2019 - CNN show better performance than Capsule Networks, dropout provides more robusteness against image noise. Trained with LoTTs images.
• [Optical Transient Object Classification in Wide Field Smal

astro313

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# Name: Bash CheatSheet for Mac OSX
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# Author: J. Le Coupanec
# Date: 2014/11/04