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One of the main problems in applying deep learning techniques to recognize activities of daily living (ADLs) based on inertial sensors is the lack of appropriately large labelled datasets to train deep learning-based models. A large amount…
Despite the growing number of gamma-ray sources detected by Fermi-LAT, about one third of the sources in each survey remains of uncertain type. We present a new deep neural network approach for the classification of unidentified or…
The main purpose of this research was to investigate how energetic processes associated with Active Galactic Nuclei are related to those due to nuclear or circumnuclear star formation activity. Photometric and spectroscopic data were used…
We investigate the process of rapid star formation quenching in a sample of 12 massive galaxies at intermediate redshift (z~0.6) that host high-velocity ionized gas outflows (v>1000 km/s). We conclude that these fast outflows are most…
What main mechanisms set the star formation rate (SFR) of galaxies? This PhD thesis is a quest into the influences of gas and active galactic nuclei (AGNs) on the SFR, with particular focus on massive galaxies at z~2. First, a new code if…
Using an advanced semi analytic model (SAM) for galaxy formation, we have investigated the statistical effects of assuming two different mechanisms for triggering AGN activity on the properties of AGN host galaxies. We have considered a…
We train Artificial Neural Networks to classify galaxies based solely on the morphology of the galaxy images as they appear on blue survey plates. The images are reduced and morphological features such as bulge size and the number of arms…
In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each…
(abridged) The clustering properties of galaxies belonging to different luminosity ranges or having different morphological types are different. These characteristics or `marks' permit to understand the galaxy catalogs that carry all this…
Despite the recent success of deep neural networks, it remains challenging to effectively model the long-tail class distribution in visual recognition tasks. To address this problem, we first investigate the performance bottleneck of the…
We develop a method ('Galactic Archaeology Neural Network', GANN) based on neural network models (NNMs) to identify accreted stars in galactic discs by only their chemical fingerprint and age, using a suite of simulated galaxies from the…
Fine-grained image recognition is central to many multimedia tasks such as search, retrieval and captioning. Unfortunately, these tasks are still challenging since the appearance of samples of the same class can be more different than those…
We produce a kinematic analysis of AGN-hosting cluster galaxies from a sample 33 galaxy clusters selected using the X-ray Clusters Database (BAX) and populated with galaxies from the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). The…
Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physically motivated prescriptions. They have also proven to be an efficient alternative for generating…
We investigate the physical nature of active galactic nuclei (AGNs) using machine learning (ML) tools. We show that the redshift, $z$, bolometric luminosity, $L_{\rm Bol}$, central mass of the supermassive black hole (SMBH), $M_{\rm BH}$,…
Human activity recognition is critical for applications such as early intervention and health analytics. Traditional activity recognition relies on inertial measurement units (IMUs), which are resource intensive and require calibration.…
Convolutional neural networks are nowadays witnessing a major success in different pattern recognition problems. These learning models were basically designed to handle vectorial data such as images but their extension to non-vectorial and…
We investigate the possible link between mergers and the enhanced activity of supermassive black holes (SMBHs) at the centre of galaxies, by comparing the merger fraction of a local sample (0.003 =< z < 0.03) of active galaxies - 59 active…
We have conducted a new spectroscopic survey to characterize the nature of nuclear activity in Hickson Compact Groups (HCGs) galaxies and establish its frequency. We have obtained new intermediate resolution optical spectroscopy for 200…
Testing theories of hierarchical structure formation requires estimating the distribution of galaxy morphologies and its change with redshift. One aspect of this investigation involves identifying galaxies with disturbed morphologies (e.g.,…