38 citations · 162 across the 20 of their papers we have counts for
5 papers · 1 filter
Deep learning to improve the discovery of near-Earth asteroids in the Zwicky Transient Facility
Belén Yu Irureta-Goyena, George Helou, Jean-Paul Kneib +7
We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. O…
LTDE: The Lens Time Delay Experiment I. From pixels to light curves
Favio Neira, Frédéric Courbin, Frédéric Dux +1
Gravitationally lensed quasars offer a unique opportunity to study cosmological and extragalactic phenomena, using reliable light curves of the lensed images. This requires accurat…
lightcurver: A Python Pipeline for Precise Photometry of Multiple-Epoch Wide-Field Images
Frédéric Dux
lightcurver is a photometric pipeline for time series astronomical imaging data, designed for the semi-automatic extraction of precise light curves from small, blended targets. Suc…
Image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light-curve extraction
Martin Millon, Kevin Michalewicz, Frédéric Dux +2
We present STARRED, a Point Spread Function (PSF) reconstruction, two-channel deconvolution, and light curve extraction method designed for high-precision photometric measurements…
STARRED: a two-channel deconvolution method with Starlet regularization
Kevin Michalewicz, Martin Millon, Frédéric Dux +1
The spatial resolution of astronomical images is limited by atmospheric turbulence and diffraction in the telescope optics, resulting in blurred images. This makes it difficult to…