Publications

Signal and Image processing

Noisesniffer: a Fully Automatic Image Forgery Detector Based on Noise Analysis

Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of these operations leave traces on the noise model which enable forgery detection through noise analysis…

Marina Gardella, Pablo Musé, Jean-Michel Morel, Miguel Colom

2021 IEEE International Workshop on Biometrics and Forensics (IWBF) - 2021

Life Sciences

Folding and Intrinsic Disorder of the Receptor Tyrosine Kinase KIT Insert Domain Seen by Conventional Molecular Dynamics Simulations

The kinase insert domain (KID) of RTK KIT is the key recruitment region for downstream signalling proteins. KID, studied by molecular dynamics simulations as a cleaved polypeptide and as a native domain fused to KIT, showed intrinsic disorder…

Julie Ledoux, Alain Trouvé, Luba Tchertanov

International Journal of Molecular Sciences - 2021

Differential Geometry

Parallel Transport on Kendall Shape Spaces

Kendall shape spaces are a widely used framework for the statistical analysis of shape data arising from many domains, often requiring the parallel transport as a tool to normalise time series data or transport gradient in optimisation procedures…

Nicolas Guigui, Elodie Maignant, Alain Trouvé, Xavier Pennec

GSI 2021 - 5th conference on Geometric Science of Information - 2021

Machine Learning

Online A-optimal design and active linear regression

We consider in this paper the problem of optimal experiment design where a decision maker can choose which points to sample to obtain an estimateβ of the hidden parameter β of an underlying linear model. The key challenge of this work lies in the…

Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet

International Conference on Machine Learning - 2021

Signal and Image processing

Forgery Detection in Digital Images by Multi-Scale Noise Estimation

A complex processing chain is applied from the moment a raw image is acquired untilthe final image is obtained. This process transforms the originally Poisson-distributed noise into acomplex noise model. Noise inconsistency analysis is a rich source…

Marina Gardella, Pablo Musé, Jean-Michel Morel, Miguel Colom

Journal of Imaging - 2021

Analysis of PDEs

Second order monotone finite differences discretization of linear anisotropic differential operators

We design adaptive finite differences discretizations, which are degenerate elliptic and second order consistent, of linear and quasi-linear partial differential operators featuring both a first order term and an anisotropic second order term. Our…

Frédéric Bonnans, Guillaume Bonnet, Jean-Marie Mirebeau

Mathematics of Computation - 2021

Computer Vision and Pattern Recognition

Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery

This paper proposes a system for automatic surface volume monitoring from time series of SkySat pushframe imagery. A specific challenge of building and comparing large 3D models from SkySat data is to correct inconsistencies between the camera…

Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis, Gabriele Facciolo

IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021 - 2021

Life Sciences

Folding and Intrinsic Disorder of the Receptor Tyrosine Kinase KIT Insert Domain Seen by Conventional Molecular Dynamics Simulations

Julie Ledoux, Alain Trouvé, Luba Tchertanov

International Journal of Molecular Sciences - 2021

Mathematics

Making the most of your day: online learning for optimal allocation of time

We study online learning for optimal allocation when the resource to be allocated is time. Examples of possible applications include a driver filling a day with rides, a landlord renting an estate, etc. Following our initial motivation, a driver…

Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini

NeurIPS - 2021

Neurobiology

A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex

A fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general…

Anton V Chizhov, Lyle J Graham

PLoS Computational Biology - 2021