86 citations · 586 across the 25 of their papers we have counts for
25 papers
Machine learning technique for morphological classification of galaxies from the SDSS. III. Image-based inference of detailed features
V. Khramtsov, I. B. Vavilova, D. V. Dobrycheva +5
This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploit…
Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02<z<0.1
I. B. Vavilova, V. Khramtsov, D. V. Dobrycheva +3
We applied the image-based approach with a convolutional neural network model to the sample of low-redshifts galaxies with from the SDSS DR9. We divided i…
The Voronoi tessellation method in astronomy
Irina Vavilova, Andrii Elyiv, Daria Dobrycheva +1
The Voronoi tessellation is a natural way of space segmentation, which has many applications in various fields of science and technology, as well as in social sciences and visual a…
Machine-learning computation of distance modulus for local galaxies
A. Elyiv, O. Melnyk, I. Vavilova +2
Quickly growing computing facilities and an increasing number of extragalactic observations encourage the application of data-driven approaches to uncover hidden relations from ast…
The XXL Survey: XXVII. The 3XLSS point source catalogue
L. Chiappetti, S. Fotopoulou, C. Lidman +35
We present the version of the point source catalogue of the XXL Survey that was used, in part, in the first series of XXL papers. In this paper we release, in our database in Milan…
The XXL Survey: XXX. Characterisation of the XLSSsC N01 supercluster and analysis of the galaxy stellar populations
V. Guglielmo, B. M. Poggianti, B. Vulcani +34
Superclusters form from the largest enhancements in the primordial density perturbation field and extend for tens of Mpc, tracing the large-scale structure of the Universe. We char…