6 citations · 14 across the 13 of their papers we have counts for
6 papers · 1 filter
MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
Mohamad Jouni, Mauro Dalla Mura, Lucas Drumetz +1
Hyperspectral unmixing allows representing mixed pixels as a set of pure materials weighted by their abundances. Spectral features alone are often insufficient, so it is common to…
Neural Koopman prior for data assimilation
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
With the increasing availability of large scale datasets, computational power and tools like automatic differentiation and expressive neural network architectures, sequential data…
Model-based demosaicking for acquisitions by a RGBW color filter array
Matthieu Muller, Daniele Picone, Mauro Dalla Mura +1
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…
Learning Sentinel-2 reflectance dynamics for data-driven assimilation and forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +2
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,…
Slow slip detection with deep learning in multi-station raw geodetic time series validated against tremors in Cascadia
Giuseppe Costantino, Sophie Giffard-Roisin, Mathilde Radiguet +3
Slow slip events (SSEs) originate from a slow slippage on faults that lasts from a few days to years. A systematic and complete mapping of SSEs is key to characterizing the slip sp…
Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
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 phys…