Related papers: A neural network-based methodology to select young…

(Abridged) Photometry of archival Spitzer observations of the Large Magellanic Cloud (LMC) are used to search for young stellar objects (YSOs). Simple mid-infrared selection criteria were used to exclude most normal and evolved stars and…

A novel general neural network (GNN) is proposed for two-class data mining in this study. In a GNN, each attribute in the dataset is treated as a node, with each pair of nodes being connected by an arc. The reliability is of each arc, which…

In this paper we present an efficient computer aided mass classification method in digitized mammograms using Artificial Neural Network (ANN), which performs benign-malignant classification on region of interest (ROI) that contains mass.…

The artificial neural network (ANN) is a well-established mathematical technique for data prediction, based on the identification of correlations and pattern recognition in input training sets. We present the application of ANNs to predict…

In order to develop a pipeline for automated classification of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an artificial neural network (ANN) technique for classifying stars by using synthetic spectra in the UV…

Modelling the complex physics of the Interstellar Medium (ISM) in the context of large-scale numerical simulations is a challenging task. A number of methods have been proposed to embed a description of the ISM into different codes. We…

We present a supervised machine learning methodology to classify stellar populations in the Local Group dwarf-irregular galaxy NGC6822. Near-IR colours (J-H, H-K, and J-K), K-band magnitudes and far-IR surface brightness (at 70 and 160…

The 7 and 15 um observations of selected fields in the Galactic Plane obtained with ISOCAM during the ISOGAL program offer an unique possibility to search for previously unknown YSOs, undetected by IRAS because of lower sensitivity or…

A naive Bayes classifier for identifying Class II YSOs has been constructed and applied to a region of the Northern Galactic Plane containing 8 million sources with good quality Gaia EDR3 parallaxes. The classifier uses the five features:…

The YSOVAR (Young Stellar Object VARiability) Spitzer Space Telescope observing program obtained the first extensive mid-infrared (3.6 & 4.5 um) time-series photometry of the Orion Nebula Cluster plus smaller footprints in eleven other…

Over the past decade, deep neural networks (DNNs) have demonstrated remarkable performance in a variety of applications. As we try to solve more advanced problems, increasing demands for computing and power resources has become inevitable.…

We describe an Artificial Neural Network (ANN) approach to classification of galaxy images and spectra. ANNs can replicate the classification of galaxy images by a human expert to the same degree of agreement as that between two human…

We present ~120,000 Spitzer/IRAC candidate young stellar objects (YSOs) based on surveys of the Galactic midplane between l~255 deg and 110 deg, including the GLIMPSE I, II, and 3D, Vela-Carina, Cygnus X, and SMOG surveys (613 square…

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…

We consider the problem in Synthetic Aperture RADAR (SAR) of identifying and classifying objects located on the ground by means of Convolutional Neural Networks (CNNs). Specifically, we adopt a single scattering approximation to classify…

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data…

We present the initial results of our investigation of the star-forming complex W49, one of the youngest and most luminous massive star forming regions in our Galaxy. We used Spitzer/Infrared Array Camera (IRAC) data to investigate massive…

The interpretation of observations of atomic and molecular tracers in the galactic and extragalactic interstellar medium (ISM) requires comparisons with state-of-the-art astrophysical models to infer some physical conditions. Usually, ISM…

We use various analytical techniques to study Young Stellar Objects (YSOs) in an area of approximately $10' \times 10'$ in the IRAS 18456-0223 star-forming region. We use archival optical (Gaia DR3) and infrared (2MASS, UKIDSS, Spitzer,…

We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an…