no code implementations • 6 May 2024 • Giuseppe Costantino, Sophie Giffard-Roisin, Mauro Dalla Mura, Anne Socquet
Among the signals affecting GNSS data, slow slip events (SSEs) are of interest to seismologists.
1 code implementation • 11 Mar 2024 • Anthony Frion, Lucas Drumetz, Guillaume Tochon, Mauro Dalla Mura, Albdeldjalil Aïssa El Bey
In the context of an increasing popularity of data-driven models to represent dynamical systems, many machine learning-based implementations of the Koopman operator have recently been proposed.
2 code implementations • 5 Oct 2023 • Mohamad Jouni, Mauro Dalla Mura, Lucas Drumetz, Pierre Comon
Matrix models become insufficient when the hyperspectral image (HSI) is represented as a high-order tensor with additional features in a multimodal, multifeature framework.
1 code implementation • 11 Sep 2023 • Anthony Frion, Lucas Drumetz, Mauro Dalla Mura, Guillaume Tochon, Abdeldjalil Aïssa El Bey
With the increasing availability of large scale datasets, computational power and tools like automatic differentiation and expressive neural network architectures, sequential data are now often treated in a data-driven way, with a dynamical model trained from the observation data.
no code implementations • 2 Jun 2023 • Matthieu Muller, Daniele Picone, Mauro Dalla Mura, Magnus O Ulfarsson
Microsatellites and drones are often equipped with digital cameras whose sensing system is based on color filter arrays (CFAs), which define a pattern of color filter overlaid over the focal plane.
1 code implementation • 5 May 2023 • Anthony Frion, Lucas Drumetz, Guillaume Tochon, Mauro Dalla Mura, Abdeldjalil Aïssa El Bey
Over the last few years, massive amounts of satellite multispectral and hyperspectral images covering the Earth's surface have been made publicly available for scientific purpose, for example through the European Copernicus project.
no code implementations • 13 Mar 2023 • Anthony Frion, Lucas Drumetz, Mauro Dalla Mura, Guillaume Tochon, Abdeldjalil Aissa El Bey
Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying physics.
1 code implementation • 3 Sep 2022 • Daniele Picone, Mauro Dalla Mura, Laurent Condat
Novel optical imaging devices allow for hybrid acquisition modalities such as compressed acquisitions with locally different spatial and spectral resolutions captured by a single focal plane array.
no code implementations • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 • Gemine Vivone, Mauro Dalla Mura, Andrea Garzelli, Fabio Pacifici
Comparative evaluation is a requirement for reproducible science and objective assessment of new algorithms.
no code implementations • 4 Jun 2019 • Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura, Jefersson A. dos Santos
Results show that the proposed DeepMorphNets is a promising technique that can learn distinct features when compared to the ones learned by current deep learning methods.
1 code implementation • 11 Apr 2018 • Keiller Nogueira, Mauro Dalla Mura, Jocelyn Chanussot, William R. Schwartz, Jefersson A. dos Santos
A systematic evaluation of the proposed algorithm is conducted using four high-resolution remote sensing datasets with very distinct properties.