Related papers: A morphological segmentation approach to determini…
Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most…
We have measured the fraction of bars in nearby spiral galaxies using near-infrared J, H, and K_s images of 151 spiral galaxies from 2MASS. This local sample provides an anchor for the study of the evolution of the bar fraction and bar…
Galaxy appearances reveal the physics of how they formed and evolved. Machine learning models can now exploit galaxies' information-rich morphologies to predict physical properties directly from image cutouts. Learning the relationship…
Different spiral generation mechanisms are expected to produce different morphological and kinematic features. In this first paper in a series we carefully study the parameters of spiral structure in 155 face-on spiral galaxies, selected…
Morphological classification conveys abundant information on the formation, evolution, and environment of galaxies. In this work, we refine the two-step galaxy morphological classification framework ({\tt\string USmorph}), which employs a…
By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COSMOS-DASH field, which includes 17292 galaxies with stellar…
Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…
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,…
Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has attracted the interest of the research community for a long time because morphological changes in these structures are related to different neurodegenerative…
We propose a new method to estimate the photometric redshift of galaxies by using the full galaxy image in each measured band. This method draws from the latest techniques and advances in machine learning, in particular Deep Neural…
We present a quantitative method to classify galaxies, based on multi-wavelength data and elaborated from the properties of nearby galaxies. Our objective is to define an evolutionary method that can be used for low and high redshift…
We present the first study of bars in the local Universe, based on the Sloan Digitized Sky Survey (SDSS). The large sample of ~5000 local galaxies provides the largest study to date of local bars and minimizes the effect of cosmic variance.…
The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels…
In this paper, we look to analyse the spiral features of grand-design, multiarmed, and flocculent spiral galaxies using deep optical imaging from DESI Legacy Imaging Surveys. We explore the resulting distributions of various characteristics…
Edge-on galaxies have many important applications in galactic astrophysics, but they can be difficult to identify in vast amounts of astronomical data. To facilitate the search for them, we have developed a deep learning algorithm designed…
This paper describes an automatic isophotal fitting procedure that succeeds, without the support of any visual inspection of neither the images nor the ellipticity/P.A. radial profiles, at extracting a fairly pure sample of barred LTGs…
In this work we analyse the structural and photometric properties of 21 barred simulated galaxies from the Auriga Project. These consist of Milky Way-mass magneto-hydrodynamical simulations in a $\Lambda$CDM cosmological context. In order…
The Galaxy Zoo has provided morphological data on many galaxies. Several biases have been identified in the Galaxy Zoo data. Here we report on a newly discovered selection effect: astronomers interested in studying spiral galaxies may…
Spiral structure can occupy a significant part of the galaxy, but properly accounting for it in photometric decomposition is rarely done. This may lead to significant errors in the parameters determined. To estimate how exactly neglecting…
$\bf{Purpose:}$ The goal of this study was (i) to use artificial intelligence to automate the traditionally labor-intensive process of manual segmentation of tumor regions in pathology slides performed by a pathologist and (ii) to validate…