2 citations · 2 across the 1 of their papers we have counts for
4 papers
Machine Learning vs. Spectral Energy Distribution Fitting: A Comparative Analysis of Accuracy in Stellar Mass Estimation
Vahid Asadi, Akram Hasani Zonoozi, Hosein Haghi
Traditional spectral energy distribution (SED)-fitting methods for stellar mass estimation face persistent challenges including systematic biases and computational constraints. We…
Machine Learning Classification of COSMOS2020 Galaxies: Quiescent vs. Star-Forming
Vahid Asadi, Nima Chartab, Akram Hasani Zonoozi +4
Accurately distinguishing between quiescent and star-forming galaxies is essential for understanding galaxy evolution. Traditional methods, such as spectral energy distribution (SE…
Semi-supervised classification of stars, galaxies and quasars using K-means and random-forest approaches
Vahid Asadi, Hosein Haghi, Akram Hasani Zonoozi
Classifying stars, galaxies, and quasars is essential for understanding cosmic structure and evolution; however, the vast data from modern surveys make manual classification imprac…
Leveraging Machine Learning for Accurate and Fast Stellar Mass Estimation of Galaxies
Vahid Asadi, Akram Hasani Zonoozi, Hosein Haghi +4
Unveiling the evolutionary history of galaxies necessitates a precise understanding of their physical properties. Traditionally, astronomers achieve this through spectral energy di…