144 citations · 976 across the 23 of their papers we have counts for
5 papers · 1 filter
Mapping the Diversity of Galaxy Spectra with Deep Unsupervised Machine Learning
Hossen Teimoorinia, Finn Archinuk, Joanna Woo +2
Modern spectroscopic surveys of galaxies such as MaNGA consist of millions of diverse spectra covering different regions of thousands of galaxies. We propose and implement a deep u…
Forecasting Wavefront Corrections in an Adaptive Optics System
Rehan Hafeez, Finn Archinuk, Sébastien Fabbro +2
We use telemetry data from the Gemini North ALTAIR adaptive optics system to investigate how well the commands for wavefront correction (both Tip/Tilt and high-order turbulence) ca…
Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG
Robert W. Bickley, Connor Bottrell, Maan H. Hani +6
The Canada-France Imaging Survey (CFIS) will consist of deep, high-resolution r-band imaging over ~5000 square degrees of the sky, representing a first-rate opportunity to identify…
An astronomical image content-based recommendation system using combined deep learning models in a fully unsupervised mode
Hossen Teimoorinia, Sara Shishehchi, Ahnaf Tazwar +4
We have developed a method that maps large astronomical images onto a two-dimensional map and clusters them. A combination of various state-of-the-art machine learning (ML) algorit…
A re-assessment of strong line metallicity conversions in the machine learning era
Hossen Teimoorinia, Mansoureh Jalilkhany, Jillian M. Scudder +2
Strong line metallicity calibrations are widely used to determine the gas phase metallicities of individual HII regions and entire galaxies. Over a decade ago, based on the Sloan D…