21 citations · 30 across the 4 of their papers we have counts for
6 papers
Detection of Abnormal Vessel Behaviours from AIS data using GeoTrackNet: from the Laboratory to the Ocean
Duong Nguyen, Matthieu Simonin, Guillaume Hajduch +3
The constant growth of maritime traffic leads to the need of automatic anomaly detection, which has been attracting great research attention. Information provided by AIS (Automatic…
Joint learning of variational representations and solvers for inverse problems with partially-observed data
Ronan Fablet, Lucas Drumetz, Francois Rousseau
Designing appropriate variational regularization schemes is a crucial part of solving inverse problems, making them better-posed and guaranteeing that the solution of the associate…
PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations
Olivier Pannekoucke, Ronan Fablet
Bridging physics and deep learning is a topical challenge. While deep learning frameworks open avenues in physical science, the design of physically-consistent deep neural network…
GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection
Duong Nguyen, Rodolphe Vadaine, Guillaume Hajduch +2
Representing maritime traffic patterns and detecting anomalies from them are key to vessel monitoring and maritime situational awareness. We propose a novel approach -- referred to…
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 (…
Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection
Duong Nguyen, Oliver S. Kirsebom, Fábio Frazão +2
In this paper, we adapt Recurrent Neural Networks with Stochastic Layers, which are the state-of-the-art for generating text, music and speech, to the problem of acoustic novelty d…