23 citations · 48 across the 7 of their papers we have counts for
7 papers
Deep learning-based deconvolution for interferometric radio transient reconstruction
Benjamin Naoto Chiche, Julien N. Girard, Joana Frontera-Pons +2
Radio astronomy is currently thriving with new large ground-based radio telescopes coming online in preparation for the upcoming Square Kilometre Array (SKA). Facilities like LOFAR…
Neural Network predictions of inclusive electron-nucleus cross sections
O. Al Hammal, M. Martini, J. Frontera-Pons +2
We investigate whether a neural network approach can reproduce and predict the electron-nucleus cross sections in the kinematical domain of present and future accelerator-based neu…
Stable Long-Term Recurrent Video Super-Resolution
Benjamin Naoto Chiche, Arnaud Woiselle, Joana Frontera-Pons +1
Recurrent models have gained popularity in deep learning (DL) based video super-resolution (VSR), due to their increased computational efficiency, temporal receptive field and temp…
Deep Unrolled Network for Video Super-Resolution
Benjamin Naoto Chiche, Arnaud Woiselle, Joana Frontera-Pons +1
Video super-resolution (VSR) aims to reconstruct a sequence of high-resolution (HR) images from their corresponding low-resolution (LR) versions. Traditionally, solving a VSR probl…
Representation learning for automated spectroscopic redshift estimation
Joana Frontera-Pons, Florent Sureau, Bruno Moraes +2
Determining the radial positions of galaxies up to a high accuracy depends on the correct identification of salient features in their spectra. Classical techniques for spectroscopi…
Unsupervised feature-learning for galaxy SEDs with denoising autoencoders
Joana Frontera-Pons, Florent Sureau, Jerome Bobin +1
With the increasing number of deep multi-wavelength galaxy surveys, the spectral energy distribution (SED) of galaxies has become an invaluable tool for studying the formation of t…
Adaptive non-Zero Mean Gaussian Detection and Application to Hyperspectral Imaging
Joana Frontera-Pons, Frederic Pascal, Jean-Philippe Ovarlez
Classical target detection schemes are usually obtained deriving the likelihood ratio under Gaussian hypothesis and replacing the unknown background parameters by their estimates.…