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AI and deep learning techniques are beginning to play an increasing role in astronomy as a necessary tool to deal with the data avalanche. Here we describe an application for finding resolved Planetary Nebulae (PNe) in crowded, wide-field,…

In this work, we use artificial neural networks (ANNs) to recognize the material composition, sizes of nanoparticles and their concentrations in different media with high accuracy, solely from the absorbance spectrum of a macroscopic…

JWST has revealed diverse new populations of high-redshift ($z\sim4-11$) AGN and extreme star-forming galaxies that challenge current models. In this paper, we use rest-frame UV emission-line diagnostics to identify AGN candidates and other…

Classification of stars and galaxies is a well-known astronomical problem that has been treated using different approaches, most of them relying on morphological information. In this paper, we tackle this issue using the low-resolution…

High-energy radiation from the Sun governs the behavior of Earth's upper atmosphere and such radiation from any planet-hosting star can drive the long-term evolution of a planetary atmosphere. However, much of this radiation is unobservable…

Extragalactic planetary nebulae (PNe) are detectable through relatively strong nebulous [OIII] emission and act as direct probes into the local stellar population. Because they have an apparently universal invariant magnitude cut-off, PNe…

The ultraviolet (UV) to sub-millimetre (submm) spectral energy distribution of galaxies can be roughly divided into two sections: the stellar emission (attenuated by dust) at UV to near-infrared wavelengths and dust emission at longer…

We present the result of a spectroscopic campaign targeting Active Galactic Nucleus (AGN) candidates selected using a novel unsupervised machine-learning (ML) algorithm trained on optical and mid-infrared (mid-IR) photometry. AGN candidates…

Up to 150000 asteroids will be visible in the images of the ESA Euclid space telescope, and the instruments of Euclid offer multiband visual to near-infrared photometry and slitless spectra of these objects. Most asteroids will appear as…

(abridged) The overwhelming majority of diagnostic tools for galactic activity are focused on active galaxies. Passive or dormant galaxies are often excluded from these diagnostics which usually employ emission line features. In this work,…

The creation of a 3D map of the bulge using RRLyrae (RRL) is one of the main goals of the VVV(X) surveys. The overwhelming number of sources under analysis request the use of automatic procedures. In this context, previous works introduced…

Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts. The classifier uses the…

GALEX, the first all sky imaging UV satellite, has imaged a large part of the sky providing an excellent opportunity for studying UV star counts. The aim of our study is to investigate in detail the observed UV star counts obtained by GALEX…

Artificial neural networks (ANN) have different applications in Astronomy, including data reduction and data mining. In this work we propose the use ANNs in the identification of stellar model solutions. We illustrate this method, by…

The reliability of infrared (IR) and ultraviolet (UV) emissions to measure star formation rates in galaxies is investigated for a large sample of galaxies observed with the SPIRE and PACS instruments on Herschel as part of the HerMES…

We present the results of the first spectroscopic follow-up of 132 optically blue UV-excess sources selected from the UV-excess survey of the Northern Galactic Plane (UVEX). The UV-excess spectra are classified into different populations…

We classify the spectral energy distributions (SEDs) of 431,038 sources in the 9 sq. deg Bootes field of the NOAO Deep Wide-Field Survey (NDWFS). There are up to 17 bands of data available per source, including ultraviolet (GALEX), optical…

The aim of this work is to develop a comprehensive method for classifying sources in large sky surveys and we apply the techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS). Using the optical (u*, g', r', i') and NIR data…

A Feed Forward Error Back Propagation Artificial Neural Network(ANN) algorithm is developed for electron/positron identification in a wide momentum region (10 - 300 GeV/c). The method was proposed for the Transition Radiation Detector of…

Due to the latest advances in technology, telescopes with significant sky coverage will produce millions of astronomical alerts per night that must be classified both rapidly and automatically. Currently, classification consists of…