Transfer learning with a Zoobot CNN on SDSS DR18 data identifies 3,679 lopsided spiral galaxies at 87% test accuracy, with lopsided systems showing higher star formation, bluer colors, lower mass and concentration.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Visual inspection of CNN outputs from SDSS produces verified catalogues of 612 merging, 9372 irregular, 16822 edge-on, 575 dust-lane, 811 barred and 2150 ringed galaxies at 0.02<z<0.1 together with BPT-based nuclear activity types.
citing papers explorer
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Identifying lopsidedness in spiral galaxies using a Deep Convolutional Neural Network
Transfer learning with a Zoobot CNN on SDSS DR18 data identifies 3,679 lopsided spiral galaxies at 87% test accuracy, with lopsided systems showing higher star formation, bluer colors, lower mass and concentration.
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Machine learning technique for morphological classification of galaxies from SDSS. IV. Visual inspection vs CNN for merging, irregular, edge-on, barred, ringed, and with dust lanes galaxies at 0.02<z<0.1
Visual inspection of CNN outputs from SDSS produces verified catalogues of 612 merging, 9372 irregular, 16822 edge-on, 575 dust-lane, 811 barred and 2150 ringed galaxies at 0.02<z<0.1 together with BPT-based nuclear activity types.