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

Modern cosmological simulations model the universe with increasing sophistication and at higher spatial and temporal resolutions. These enhancements permit detailed comparisons between the simulation outputs and real observational data.…

Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey (SDSS) have resulted in the availability of very large collections of images,…

Lens modeling is the key to successful and meaningful automated strong galaxy-scale gravitational lens detection. We have implemented a lens-modeling "robot" that treats every bright red galaxy (BRG) in a large imaging survey as a potential…

The large number of galaxies imaged by digital sky surveys reinforces the need for computational methods for analyzing galaxy morphology. While the morphology of most galaxies can be associated with a stage on the Hubble sequence,…

The morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings with it the need for the use of…

We present a new sample of galaxy groups identified in the Sloan Digital Sky Survey Data Release 3. Following previous works we use the well tested friend-of-friend algorithm developed by Huchra & Geller which take into account the number…

We present a catalogue of morphologically classified bright galaxies in the north equatorial stripe (230 deg$^2$) derived from the Third Data Release of the Sloan Digital Sky Survey (SDSS). Morphological classification is performed by…

We present morphological classifications based on Galaxy Zoo analysis of 71,052 galaxies with imaging from the United Kingdom Infrared Telescope Infrared Deep Sky Survey (UKIDSS). Galaxies were selected out of the Galaxy Zoo 2 (GZ2) sample,…

In recent years, large scale data intensive astronomical surveys have resulted in more detailed images being produced than scientists can manually classify. Even attempts to crowd-source this work will soon be outpaced by the large amount…

We present the results of an imaging programme of distant galaxies (z~0.8) at high spatial resolution (~0.1").We observed 7 fields of 1'*1' with the NACO Adaptive Optics system (VLT) in Ks (2.16um) band with typical V ~ 14 guide stars and…

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer…

The aim of this study is to determine the fractions of different spiral galaxy types, especially bulgeless disks, from a complete and homogeneous sample of 15127 edge-on disk galaxies extracted from the sixth data release from the Sloan…

Rings are important and characteristic features of disc-shaped galaxies. This paper is the first in a series which re-visits galactic rings with the goals of further understanding the nature of the features and for examining their role in…

(Abridged) We analyse Hubble Space Telescope images of a complete sample of 341 galaxies drawn from both the Canada France and Autofib/Low Dispersion Survey Spectrograph ground-based redshift surveys. We discuss morphological…

The images of 229 galaxies in the Canada France Redshift Survey have been classified on the DDO system. These observations were combined with previous classifications of galaxies with known redshifts in the Hubble Deep Field. The combined…

We investigate the photometric properties of 456 bright galaxies using imaging data recorded during the commissioning phase of the Sloan Digital Sky Survey (SDSS). Morphological classification is carried out by correlating results of…

We describe the application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the $u,g,r,i,$ and $z$-band images of 1519 galaxies from the Sloan Digital Sky Survey. We utilize…

We present an enhanced unsupervised machine learning (UML) module within our previous \texttt{USmorph} classification framework featuring two components: (1) hierarchical feature extraction via a pre-trained ConvNeXt convolutional neural…

Aims. We investigate the relationships between three main optical galaxy observables (spectral properties, colours, and morphology), exploiting the data set provided by the COSMOS/zCOSMOS survey. The purpose of this paper is to define a…

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…