2 citations · 3 across the 6 of their papers we have counts for
7 papers
A Study on the Evolution of NGC6822. I. Investigating the Star Formation History through Evolved Stellar Populations
Fatemeh Khatamsaz, Mahdi Abdollahi, Atefeh Javadi +4
NGC6822 is an isolated dwarf irregular galaxy in the Local Group at a distance of 490 kpc . In this paper, we derived the star formation history (SFH) of NGC6822 employing a…
Metallicity Effects on Machine Learning Classification of Dusty Stellar Sources in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
Differences in metallicity between the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC) offer an opportunity to examine whether environmental metallicity affects t…
Comparison of Photometric and Spectroscopic Labels in Classifying Dusty Stellar Sources Using Machine Learning in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
Dusty stellar sources, including young stellar objects (YSOs) and evolved stars such as oxygen- and carbon-rich AGBs (OAGBs, CAGBs), red supergiants (RSGs), and post-AGB stars (PAG…
Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +7
Dusty stellar point sources are a significant stage in stellar evolution and contribute to the metal enrichment of galaxies. These objects can be classified using photometric and s…
Machine Learning Classification of Young Stellar Objects and Evolved Stars in the Magellanic Clouds Using the Probabilistic Random Forest Classifier
Sepideh Ghaziasgar, Mahdi Abdollahi, Atefeh Javadi +4
The Magellanic Clouds (MCs) are excellent locations to study stellar dust emission and its contribution to galaxy evolution. Through spectral and photometric classification, MCs ca…
Spectral identification and classification of dusty stellar sources using spectroscopic and multiwavelength observations through machine learning
Sepideh Ghaziasgar, Amirhossein Masoudnezhad, Atefeh Javadi +3
We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolv…
From evolved Long-Period-Variable stars to the evolution of M31
Maryam Torki, Mahdieh Navabi, Atefeh Javadi +3
One of the ways to understand the genesis and evolution of the universe is to know how galaxies have formed and evolved. In this regard, the study of star formation history (SFH) p…