Laurent Jacques

research

∙ 06/22/2023

Interferometric lensless imaging: rank-one projections of image frequencies with speckle illuminations

Lensless illumination single-pixel imaging with a multicore fiber (MCF) ...

0 Olivier Leblanc, et al. ∙

research

∙ 03/15/2023

Learning to Reconstruct Signals From Binary Measurements

Recent advances in unsupervised learning have highlighted the possibilit...

0 Julián Tachella, et al. ∙

research

∙ 05/17/2022

ROP inception: signal estimation with quadratic random sketching

Rank-one projections (ROP) of matrices and quadratic random sketching of...

0 Rémi Delogne, et al. ∙

research

∙ 07/31/2021

The Separation Capacity of Random Neural Networks

Neural networks with random weights appear in a variety of machine learn...

0 Sjoerd Dirksen, et al. ∙

research

∙ 04/22/2021

Compressive lensless endoscopy with partial speckle scanning

The lensless endoscope (LE) is a promising device to acquire in vivo ima...

0 Stéphanie Guérit, et al. ∙

research

∙ 04/20/2021

Asymmetric compressive learning guarantees with applications to quantized sketches

The compressive learning framework reduces the computational cost of tra...

0 Vincent Schellekens, et al. ∙

research

∙ 01/29/2021

Morphological components analysis for circumstellar disks imaging

Recent developments in astronomical observations enable direct imaging o...

0 Benoît Pairet, et al. ∙

research

∙ 11/12/2020

Keep the phase! Signal recovery in phase-only compressive sensing

We demonstrate that a sparse signal can be estimated from the phase of c...

0 Laurent Jacques, et al. ∙

research

∙ 09/14/2020

When compressive learning fails: blame the decoder or the sketch?

In compressive learning, a mixture model (a set of centroids or a Gaussi...

0 Vincent Schellekens, et al. ∙

research

∙ 08/17/2020

One Bit to Rule Them All : Binarizing the Reconstruction in 1-bit Compressive Sensing

This work focuses on the reconstruction of sparse signals from their 1-b...

0 Thomas Feuillen, et al. ∙

research

∙ 08/04/2020

Sketching Datasets for Large-Scale Learning (long version)

This article considers "sketched learning," or "compressive learning," a...

46 Rémi Gribonval, et al. ∙

research

∙ 04/14/2020

Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines

Many signal processing and machine learning applications are built from ...

0 Vincent Schellekens, et al. ∙

research

∙ 02/12/2020

Compressive Learning of Generative Networks

Generative networks implicitly approximate complex densities from their ...

0 Vincent Schellekens, et al. ∙

research

∙ 01/08/2020

The importance of phase in complex compressive sensing

We consider the question of estimating a real low-complexity signal (suc...

0 Laurent Jacques, et al. ∙

research

∙ 12/05/2019

(l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements

This letter analyzes the performances of a simple reconstruction method,...

0 Thomas Feuillen, et al. ∙

research

∙ 07/23/2019

Close Encounters of the Binary Kind: Signal Reconstruction Guarantees for Compressive Hadamard Sampling with Haar Wavelet Basis

We investigate the problems of 1-D and 2-D signal recovery from subsampl...

0 Amirafshar Moshtaghpour, et al. ∙

research

∙ 01/19/2019

One-Bit Sensing of Low-Rank and Bisparse Matrices

This note studies the worst-case recovery error of low-rank and bisparse...

0 Simon Foucart, et al. ∙

research

∙ 12/04/2018

Compressive Classification (Machine Learning without learning)

Compressive learning is a framework where (so far unsupervised) learning...

0 Vincent Schellekens, et al. ∙

research

∙ 12/03/2018

Proceedings of the fourth "international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques" (iTWIST'18)

The iTWIST workshop series aim at fostering collaboration between intern...

0 Sandrine Anthoine, et al. ∙

research

∙ 10/31/2018

Compressive Single-pixel Fourier Transform Imaging using Structured Illumination

Single Pixel (SP) imaging is now a reality in many applications, e.g., b...

0 Amirafshar Moshtaghpour, et al. ∙

research

∙ 10/29/2018

Compressive Sampling Approach for Image Acquisition with Lensless Endoscope

The lensless endoscope is a promising device designed to image tissues i...

0 Stéphanie Guérit, et al. ∙

research

∙ 09/04/2018

Compressive Hyperspectral Imaging: Fourier Transform Interferometry meets Single Pixel Camera

This paper introduces a single-pixel HyperSpectral (HS) imaging framewor...

0 Amirafshar Moshtaghpour, et al. ∙

research

∙ 05/11/2018

Taking the edge off quantization: projected back projection in dithered compressive sensing

Quantized compressive sensing (QCS) deals with the problem of representi...

0 Chunlei Xu, et al. ∙

research

∙ 04/26/2018

Quantized Compressive K-Means

The recent framework of compressive statistical learning aims at designi...

0 Vincent Schellekens, et al. ∙

research

∙ 03/08/2018

Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy

Fourier Transform Interferometry (FTI) is an interferometric procedure f...

0 Amirafshar Moshtaghpour, et al. ∙

research

∙ 02/06/2018

Multispectral Compressive Imaging Strategies using Fabry-Pérot Filtered Sensors

This paper introduces two acquisition device architectures for multispec...

0 Kevin Degraux, et al. ∙

research

∙ 01/17/2018

Quantized Compressive Sensing with RIP Matrices: The Benefit of Dithering

In Compressive Sensing theory and its applications, quantization of sign...

0 Chunlei Xu, et al. ∙

research

∙ 08/05/2016

Blind Deconvolution of PET Images using Anatomical Priors

Images from positron emission tomography (PET) provide metabolic informa...

0 Stéphanie Guérit, et al. ∙

research

∙ 02/18/2016

Multi-resolution Compressive Sensing Reconstruction

We consider the problem of reconstructing an image from compressive meas...

0 Adriana González, et al. ∙

research

∙ 02/17/2016

Cell segmentation with random ferns and graph-cuts

The progress in imaging techniques have allowed the study of various asp...

0 Arnaud Browet, et al. ∙

research

∙ 06/16/2015

Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization

Improving the quality of positron emission tomography (PET) images, affe...

0 Stéphanie Guérit, et al. ∙

research

∙ 04/05/2015

Discriminative and Efficient Label Propagation on Complementary Graphs for Multi-Object Tracking

Given a set of detections, detected at each time instant independently, ...

0 Amit Kumar K. C., et al. ∙

research

∙ 12/19/2014

Non-parametric PSF estimation from celestial transit solar images using blind deconvolution

Context: Characterization of instrumental effects in astronomical imagin...

0 Adriana González, et al. ∙

research

∙ 06/25/2014

Compressive Imaging and Characterization of Sparse Light Deflection Maps

Light rays incident on a transparent object of uniform refractive index ...

0 Prasad Sudhakar, et al. ∙

research

∙ 12/03/2012

Compressive Schlieren Deflectometry

Schlieren deflectometry aims at characterizing the deflections undergone...

0 Prasad Sudhakar, et al. ∙

research

∙ 11/06/2012

From Bits to Images: Inversion of Local Binary Descriptors

Local Binary Descriptors are becoming more and more popular for image ma...

0 Emmanuel d'Angelo, et al. ∙

research

∙ 09/04/2012

Compressive Optical Deflectometric Tomography: A Constrained Total-Variation Minimization Approach

Optical Deflectometric Tomography (ODT) provides an accurate characteriz...

0 Adriana González, et al. ∙

research

∙ 01/27/2011

A Panorama on Multiscale Geometric Representations, Intertwining Spatial, Directional and Frequency Selectivity

The richness of natural images makes the quest for optimal representatio...

1 Laurent Jacques, et al. ∙

research

∙ 09/15/2010

Invariant Spectral Hashing of Image Saliency Graph

Image hashing is the process of associating a short vector of bits to an...

0 Maxime Taquet, et al. ∙

Laurent Jacques

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