DeepMerge: Classifying high-redshift merging galaxies with deep neural networks
Aleksandra Ćiprijanović(Fermi National Accelerator Laboratory), J. E. G. Peek(Space Telescope Science Institute), B. Nord(Fermi National Accelerator Laboratory), Gregory F. Snyder(Space Telescope Science Institute)
Cited by 56
Related Papers
DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains
|Monthly Notices of the Royal Astronomical Society|2021|46
DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images
|Astronomy and Computing|2022|21
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification
|Machine Learning Science and Technology|2022|20
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection
|Machine Learning Science and Technology|2023|17
Machine Learning and Cosmology
|arXiv (Cornell University)|2022|15