Related papers: Revisiting the Hubble sequence in the SDSS DR7 spe…

We address the problem of morphological classification of galaxies from the Galaxy Zoo DECaLS dataset using classical machine learning techniques. Our approach employs a dimensionality reduction method followed by a classical classifier to…

Aims:The Gaia astrometric survey mission will, as a consequence of its scanning law, obtain low resolution optical (330-1000 nm) spectrophotometry of several million unresolved galaxies brighter than V=22. We present the first steps in a…

Galaxy morphology offers significant insights into the evolutionary pathways and underlying physics of galaxies. As astronomical data grows with surveys such as Euclid and Vera C. Rubin , there is a need for tools to classify and analyze…

The morphological classification of galaxies provides vital physical information about the orbital motions of stars in galaxies, and correlates in interesting ways with star formation history, and other physical properties. Galaxy…

We study the morphology of luminous and massive galaxies at 0.3<z<0.7 targeted in the Baryon Oscillation Spectroscopic Survey (BOSS) using publicly available Hubble Space Telescope imaging from COSMOS. Our sample (240 objects) provides a…

We present a detailed visual morphological classification for the 4614 MaNGA galaxies in SDSS Data Release 15, using image mosaics generated from a combination of r-band (SDSS and deeper DESI Legacy Surveys) images and their digital…

The morphology of a galaxy has been shown to encode the evolutionary history and correlates strongly with physical properties such as stellar mass, star formation rates and past merger events. While the majority of galaxies in the local…

We present a catalog of visual like H-band morphologies of $\sim50.000$ galaxies ($H_{f160w}<24.5$) in the 5 CANDELS fields (GOODS-N, GOODS-S, UDS, EGS and COSMOS). Morphologies are estimated with Convolutional Neural Networks (ConvNets).…

We present the largest, most homogeneous catalogue of merging galaxies in the nearby universe obtained through the Galaxy Zoo project - an interface on the world-wide web enabling large-scale morphological classification of galaxies through…

In this study, we investigate the morphology of galaxies in the TNG100 simulation by applying mock observation techniques and compare the results with the observational data from the Sloan Digital Sky Survey (SDSS). By employing a…

Aims. We intend to compile a new galaxy group and cluster sample of the latest available SDSS data, adding several parameter for the purpose of studying the supercluster network, galaxy and group evolution, and their connection to the…

This paper is the third which examines galaxy morphology from the point of view of comprehensive de Vaucouleurs revised Hubble-Sandage (CVRHS) classification, a variation on the original de Vaucouleurs classification volume that accounts…

This paper presents machine learning experiments performed over results of galaxy classification into elliptical (E) and spiral (S) with morphological parameters: concetration (CN), assimetry metrics (A3), smoothness metrics (S3), entropy…

Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated…

We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to train an optimised random forest classifier using photometry from the SDSS and the Widefield Infrared Survey Explorer (WISE). We applied this…

The Galform semi-analytic model of galaxy formation is used to explore the mechanisms primarily responsible for the three types of galaxies seen in the local universe: bulge, bulge+disk and disk, identified with the visual morphological…

We study the morphology of a set of superclusters drawn from the SDSS DR7. We calculate the luminosity density field to determine superclusters from a flux- limited sample of galaxies from SDSS DR7, and select superclusters with 300 and…

We compare the Hubble type and the spectroscopic class of the galaxies with spectra in SDSS/DR7. As it is long known, elliptical galaxies tend to be red whereas spiral galaxies tend to be blue, however, this relationship presents a large…

We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN can learn from galaxy images with uncertain labels and…

I review here past and present research on clusters and groups of galaxies within the Sloan Digital Sky Survey (SDSS). In particular, I discuss the C4 algorithm which is designed to search for clusters within a 7-dimensional data-space,…