6 citations · 14 across the 13 of their papers we have counts for
18 papers
Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +3
Neural Koopman autoencoder models have been shown to successfully build a latent embedding with linear dynamics for arbitrary dynamical systems, enabling strong performance in long…
XCalib Depth-Guided Geometric Optimization for Dense Thermal-Visible Video Registration
Aurelien Godet, Gabriel Jobert, Mauro Dalla Mura
Image registration is a vital preprocessing step in multimodal perception tasks, including image fusion, object detection, and semantic segmentation. In Advanced Driver- Assistance…
Lightweight Interpretable RGB-Guided Hyperspectral Super-Resolution under Real Cross-resolution Misalignment
Mohamad Jouni, Aurélien Godet, Mauro Dalla Mura
Compact snapshot hyperspectral cameras provide rich instantaneous spectral measurements for ground-level machine vision, but at lower spatial resolution than standard RGB cameras.…
Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions
Jorge Bacca, Kebin Contreras, Luis Toscano-Palomino +1
We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or interpolating video frames,…
Leveraging pretrained RGB denoisers for hyperspectral image restoration
Daniele Picone, Mohamad Jouni, Mauro Dalla-Mura
Hyperspectral image restoration faces several challenges, including limited training data, strong sensor specificity, and high spectral dimensionality. These limitations hinder the…
The data heat island effect: quantifying the impact of AI data centers in a warming world
Andrea Marinoni, Erik Cambria, Weisi Lin +6
The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable escalation of their power consumption. I…
See the past: Time-Reversed Scene Reconstruction from Thermal Traces Using Visual Language Models
Kebin Contreras, Luis Toscano-Palomino, Mauro Dalla Mura +1
Recovering the past from present observations is an intriguing challenge with potential applications in forensics and scene analysis. Thermal imaging, operating in the infrared ran…
Augmented Invertible Koopman Autoencoder for long-term time series forecasting
Anthony Frion, Lucas Drumetz, Mauro Dalla Mura +2
Following the introduction of Dynamic Mode Decomposition and its numerous extensions, many neural autoencoder-based implementations of the Koopman operator have recently been propo…
Koopman Ensembles for Probabilistic Time Series Forecasting
Anthony Frion, Lucas Drumetz, Guillaume Tochon +2
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 b…
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…
Joint demosaicing and fusion of multiresolution coded acquisitions: A unified image formation and reconstruction method
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 f…
Learning Endmember Dynamics in Multitemporal Hyperspectral Data Using a State-Space Model Formulation
Lucas Drumetz, Mauro Dalla Mura, Guillaume Tochon +1
Hyperspectral image unmixing is an inverse problem aiming at recovering the spectral signatures of pure materials of interest (called endmembers) and estimating their proportions (…
An Introduction to Deep Morphological Networks
Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura +1
The recent impressive results of deep learning-based methods on computer vision applications brought fresh air to the research and industrial community. This success is mainly due…