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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) ...
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03/15/2023
Learning to Reconstruct Signals From Binary Measurements
Recent advances in unsupervised learning have highlighted the possibilit...
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05/17/2022
ROP inception: signal estimation with quadratic random sketching
Rank-one projections (ROP) of matrices and quadratic random sketching of...
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07/31/2021
The Separation Capacity of Random Neural Networks
Neural networks with random weights appear in a variety of machine learn...
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04/22/2021
Compressive lensless endoscopy with partial speckle scanning
The lensless endoscope (LE) is a promising device to acquire in vivo ima...
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04/20/2021
Asymmetric compressive learning guarantees with applications to quantized sketches
The compressive learning framework reduces the computational cost of tra...
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01/29/2021
Morphological components analysis for circumstellar disks imaging
Recent developments in astronomical observations enable direct imaging o...
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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...
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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...
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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...
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08/04/2020
Sketching Datasets for Large-Scale Learning (long version)
This article considers "sketched learning," or "compressive learning," a...
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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 ...
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02/12/2020
Compressive Learning of Generative Networks
Generative networks implicitly approximate complex densities from their ...
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01/08/2020
The importance of phase in complex compressive sensing
We consider the question of estimating a real low-complexity signal (suc...
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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,...
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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...
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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...
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12/04/2018
Compressive Classification (Machine Learning without learning)
Compressive learning is a framework where (so far unsupervised) learning...
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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...
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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...
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10/29/2018
Compressive Sampling Approach for Image Acquisition with Lensless Endoscope
The lensless endoscope is a promising device designed to image tissues i...
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09/04/2018
Compressive Hyperspectral Imaging: Fourier Transform Interferometry meets Single Pixel Camera
This paper introduces a single-pixel HyperSpectral (HS) imaging framewor...
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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...
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04/26/2018
Quantized Compressive K-Means
The recent framework of compressive statistical learning aims at designi...
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03/08/2018
Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy
Fourier Transform Interferometry (FTI) is an interferometric procedure f...
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02/06/2018
Multispectral Compressive Imaging Strategies using Fabry-Pérot Filtered Sensors
This paper introduces two acquisition device architectures for multispec...
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01/17/2018
Quantized Compressive Sensing with RIP Matrices: The Benefit of Dithering
In Compressive Sensing theory and its applications, quantization of sign...
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08/05/2016
Blind Deconvolution of PET Images using Anatomical Priors
Images from positron emission tomography (PET) provide metabolic informa...
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02/18/2016
Multi-resolution Compressive Sensing Reconstruction
We consider the problem of reconstructing an image from compressive meas...
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02/17/2016
Cell segmentation with random ferns and graph-cuts
The progress in imaging techniques have allowed the study of various asp...
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06/16/2015
Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization
Improving the quality of positron emission tomography (PET) images, affe...
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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, ...
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12/19/2014
Non-parametric PSF estimation from celestial transit solar images using blind deconvolution
Context: Characterization of instrumental effects in astronomical imagin...
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06/25/2014
Compressive Imaging and Characterization of Sparse Light Deflection Maps
Light rays incident on a transparent object of uniform refractive index ...
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12/03/2012
Compressive Schlieren Deflectometry
Schlieren deflectometry aims at characterizing the deflections undergone...
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11/06/2012
From Bits to Images: Inversion of Local Binary Descriptors
Local Binary Descriptors are becoming more and more popular for image ma...
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09/04/2012
Compressive Optical Deflectometric Tomography: A Constrained Total-Variation Minimization Approach
Optical Deflectometric Tomography (ODT) provides an accurate characteriz...
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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...
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09/15/2010
