activity
20132024
most citedStein COnsistent Risk Estimator (SCORE) for hard thresholding

10 citations · 14 across the 8 of their papers we have counts for

collaborators

14 papers

cs.CV2024

Patch-based adaptive temporal filter and residual evaluation

Weiying Zhao, Paul Riot, Charles-Alban Deledalle +3

In coherent imaging systems, speckle is a signal-dependent noise that visually strongly degrades images' appearance. A huge amount of SAR data has been acquired from different sens…

cs.CV2023

Multitemporal SAR images change detection and visualization using RABASAR and simplified GLR

Weiying Zhao, Charles-Alban Deledalle, Loïc Denis +3

Understanding the state of changed areas requires that precise information be given about the changes. Thus, detecting different kinds of changes is important for land surface moni…

cs.LG2020★ 2 cited

WaveQ: Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization

Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah +3

As deep neural networks make their ways into different domains, their compute efficiency is becoming a first-order constraint. Deep quantization, which reduces the bitwidth of the…

math.ST2020

Low-rank matrix denoising for count data using unbiased Kullback-Leibler risk estimation

Jérémie Bigot, Charles Deledalle

Many statistical studies are concerned with the analysis of observations organized in a matrix form whose elements are count data. When these observations are assumed to follow a P…

eess.SP2019

Machine learning in acoustics: theory and applications

Michael J. Bianco, Peter Gerstoft, James Traer +4

Acoustic data provide scientific and engineering insights in fields ranging from biology and communications to ocean and Earth science. We survey the recent advances and transforma…

math.OC2019

Refitting solutions promoted by sparse analysis regularization with block penalties

Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon +1

In inverse problems, the use of an analysis regularizer induces a bias in the estimated solution. We propose a general refitting framework for removing this artifact wh…