144 citations · 976 across the 23 of their papers we have counts for
5 papers · 1 filter
Mitigating the Non-Linearities in a Pyramid Wavefront Sensor
Finn Archinuk, Rehan Hafeez, Sébastien Fabbro +2
For natural guide start adaptive optics (AO) systems, pyramid wavefront sensors (PWFSs) can provide significant increase in sensitivity over the traditional Shack-Hartmann, but at…
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…
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…
Assessment of astronomical images using combined machine learning models
Hossen Teimoorinia, J. J. Kavelaars, Stephen Gwyn +3
We present a two-component Machine Learning (ML) based approach for classifying astronomical images by data-quality via an examination of sources detected in the images and image p…
LRP2020: Machine Learning Advantages in Canadian Astrophysics
K. A. Venn, S. Fabbro, A Liu +12
The application of machine learning (ML) methods to the analysis of astrophysical datasets is on the rise, particularly as the computing power and complex algorithms become more po…