Related papers: Morphological classification of compact and extend…

We present an analysis of the far-infrared (FIR)-radio correlation within a group of nearby star-forming galaxy disks observed as part of the {\it Spitzer} Infrared Nearby Galaxies Survey (SINGS). In our study we critically test a…

Building on our previous work, we apply a U-Net Variational Autoencoder (VAE) framework to denoise galaxy images from the James Webb Space Telescope (JWST) and enhance morphological classification. This study focuses on galaxies observed up…

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because…

Current wide-area radio surveys are dominated by active galactic nuclei, yet many of these sources have no identified optical counterparts. Here we investigate whether one can constrain the nature and properties of these sources, using…

In digital forensics, file fragment classification is an important step toward completing file carving process. There exist several techniques to identify the type of file fragments without relying on meta-data, such as using features like…

Presently, deep learning and convolutional neural networks (CNNs) are widely used in the fields of image processing, image classification, object identification and many more. In this work, we implemented convolutional neural network based…

We investigate the relation between the radio (F_r) and optical (F_o) flux densities of a variety of classes of radio transients and variables, with the aim of analysing whether this information can be used, in the future, to classify such…

Identifying mergers from observational data has been a crucial aspect of studying galaxy evolution and formation. Tidal features, typically fainter than 26 ${\rm mag\,arcsec^{-2}}$, exhibit a diverse range of appearances depending on the…

We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies…

We examine morphology-separated color-mass diagrams to study the quenching of star formation in $\sim 100,000$ ($z\sim0$) Sloan Digital Sky Survey (SDSS) and $\sim 20,000$ ($z\sim1$) Cosmic Assembly Near-Infrared Deep Extragalactic Legacy…

In this work, we investigate the feasibility and effectiveness of employing deep learning algorithms for automatic recognition of the modulation type of received wireless communication signals from subsampled data. Recent work considered a…

We present the morphological catalog of galaxies in nearby clusters of the WINGS survey (Fasano et al. 2006). The catalog contains a total number of 39923 galaxies, for which we provide the automatic estimates of the morphological type…

We quantify the angular clustering of radio galaxies in the NVSS and FIRST radio surveys using the two-point correlation function and the moments of counts-in-cells - both important points of comparison with theory. These investigations…

We have undertaken a program of high-resolution imaging of high-redshift radio galaxies (HzRGs) using adaptive optics on the Canada-France-Hawaii Telescope. We report on deep imaging in J, H,and K bands of 6 HzRGs in the redshift range 1.1…

The morphologies of wide-angle tailed (WAT) radio sources (edge-darkened, C-shaped, FR I radio sources) are the result of confinement and distortion of the radio lobes by the dense X-ray-emitting gas in clusters or groups of galaxies. These…

We present MargNet, a deep learning-based classifier for identifying stars, quasars and compact galaxies using photometric parameters and images from the Sloan Digital Sky Survey (SDSS) Data Release 16 (DR16) catalogue. MargNet consists of…

We detect and study the properties of faint radio AGN in Luminous Red Galaxies (LRGs). The LRG sample comprises 760,000 objects from a catalog of LRG photometric redshifts constructed from the Sloan Digital Sky Survey (SDSS) imaging data,…

We develop a new analysis approach towards identifying related radio components and their corresponding infrared host galaxy based on unsupervised machine learning methods. By exploiting PINK, a self-organising map algorithm, we are able to…

A catalogue of 14453 radio-loud AGN with 1.4 GHz fluxes above 3.5 mJy in the redshift range 0.4<z<0.8, has been constructed from the cross-correlation of the NVSS and FIRST radio surveys with the MegaZ-LRG catalogue of luminous red galaxies…

Several ongoing and upcoming radio telescopes aim to detect either the global 21 cm signal or the 21 cm power spectrum. The extragalactic radio background, as detected by ARCADE-2 and LWA-1, suggests a strong radio background from cosmic…