World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
15025
World Ranking
10445
National Ranking
255

Overview

Michel Barlaud is affiliated with Université Côte d'Azur in France. Their research activity spans multiple disciplines, focusing primarily on the intersection of biochemistry, genetics, molecular biology, and computer science, with notable contributions to engineering as well.

The main fields of study covered in their work include:

  • Biochemistry, Genetics and Molecular Biology
  • Computer Science
  • Engineering

Within these fields, their research addresses several subfields such as:

  • Molecular Biology
  • Artificial Intelligence
  • Computational Mechanics
  • Computer Vision and Pattern Recognition
  • Complementary and alternative medicine

Barlaud's key research topics encompass:

  • Sparse and Compressive Sensing Techniques
  • Metabolomics and Mass Spectrometry Studies
  • Gene expression and cancer classification
  • Traditional Chinese Medicine Studies
  • Cancer-related molecular mechanisms research
  • Neural Networks and Applications
  • Machine Learning and Data Classification

Their recent publications demonstrate a range of applications in clinical metabolomics, bioinformatics, artificial intelligence, and biomedical fields. These include:

  • "Learning a confidence score and the latent space of a new supervised autoencoder for diagnosis and prognosis in clinical metabolomic studies" (2022, BMC Bioinformatics)
  • "Efficient projection algorithms onto the weighted ℓ1 ball" (2022, Artificial Intelligence)
  • "Primal-dual for classification with rejection (PD-CR): a novel method for classification and feature selection-an application in metabolomics studies" (2021, BMC Bioinformatics)
  • "Semi-supervised classification using a supervised autoencoder for biomedical applications" (2022, arXiv (Cornell University))
  • "Detecting subtle transcriptomic perturbations induced by lncRNAs Knock-Down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network" (2023, bioRxiv (Cold Spring Harbor Laboratory))

Frequently published venues for Barlaud's research are:

  • arXiv (Cornell University)
  • BMC Bioinformatics
  • Research Square (Research Square)
  • Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)

In collaboration, Barlaud has worked with several researchers multiple times. Notable co-authors include:

  • Cyprien Gille
  • Guillaume Perez
  • David Chardin
  • Thierry Pourcher
  • Olivier Humbert

Best Publications

  • Image coding using wavelet transform

    M. Antonini;M. Barlaud;P. Mathieu;I. Daubechies

  • Deterministic edge-preserving regularization in computed imaging

    P. Charbonnier;L. Blanc-Feraud;G. Aubert;M. Barlaud

  • Two deterministic half-quadratic regularization algorithms for computed imaging

    P. Charbonnier;L. Blanc-Feraud;G. Aubert;M. Barlaud

  • Fast k nearest neighbor search using GPU

    V. Garcia;E. Debreuve;M. Barlaud

  • IMAGE SEGMENTATION USING ACTIVE CONTOURS: CALCULUS OF VARIATIONS OR SHAPE GRADIENTS? ∗

    Gilles Aubert;Michel Barlaud;Olivier D. Faugeras;Stéphanie Jehan-Besson

  • Variational approach for edge-preserving regularization using coupled PDEs

    S. Teboul;L. Blanc-Feraud;G. Aubert;M. Barlaud

  • DREAM 2 S: Deformable Regions Driven by an Eulerian Accurate Minimization Method for Image and Video Segmentation

    Stéphanie Jehan-Besson;Michel Barlaud;Gilles Aubert

  • Pyramidal lattice vector quantization for multiscale image coding

    M. Barlaud;P. Sole;T. Gaidon;M. Antonini

  • K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching

    Vincent Garcia;Eric Debreuve;Frank Nielsen;Michel Barlaud

  • Fractal image compression based on Delaunay triangulation and vector quantization

    F. Davoine;M. Antonini;J.-M. Chassery;M. Barlaud

  • Image coding using vector quantization in the wavelet transform domain

    M. Antonini;M. Barlaud;P. Mathieu;I. Daubechies

  • Combining shape prior and statistical features for active contour segmentation

    M. Gastaud;M. Barlaud;G. Aubert

  • Space-time segmentation using level set active contours applied to myocardial gated SPECT

    E. Debreuve;M. Barlaud;G. Aubert;I. Laurette

  • Robust real-time segmentation of images and videos using a smooth-spline snake-based algorithm

    F. Precioso;M. Barlaud;T. Blu;M. Unser

  • Results on AR-modelling of nonstationary signals

    R. Charbonnier;M. Barlaud;G. Alengrin;J. Menez

  • A new regularization scheme for inverse scattering

    P. Lobel;Laure Blanc-Féraud;Christian Pichot;Michel Barlaud

  • Design of signal-adapted multidimensional lifting scheme for lossy coding

    A. Gouze;M. Antonini;M. Barlaud;B. Macq

  • Image coding using lattice vector quantization of wavelet coefficients

    M. Antonini;M. Barlaud;P. Mathieu

  • Nonlinear image processing: modeling and fast algorithm for regularization with edge detection

    L. Blanc-Feraud;P. Charbonnier;G. Aubert;M. Barlaud

  • Video object segmentation using Eulerian region-based active contours

    S. Jehan-Besson;M. Barlaud;G. Aubert

  • Detection and tracking of moving objects using a new level set based method

    S.J. Besson;M. Barlaud;G. Aubert

Frequent Co-Authors

Gilles Aubert
Gilles Aubert Université Côte d'Azur
Frank Nielsen
Frank Nielsen Sony Computer Science Laboratories
Richard Nock
Richard Nock Australian National University
Patrick L. Combettes
Patrick L. Combettes North Carolina State University
Benoît Macq
Benoît Macq Université Catholique de Louvain
Patrick Solé
Patrick Solé Centre national de la recherche scientifique, CNRS
Robert M. Gray
Robert M. Gray Stanford University
Devis Tuia
Devis Tuia École Polytechnique Fédérale de Lausanne
Thierry Blu
Thierry Blu Chinese University of Hong Kong
Janusz Konrad
Janusz Konrad Boston University

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