World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5485
World Ranking
11668
National Ranking
291

Overview

Stéphane Canu is affiliated with the Institut National des Sciences Appliquées de Rouen in France. Their research mainly spans the fields of Computer Science and Engineering, with a focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology, Statistics and Probability, and Aerospace Engineering.

The primary topics they have explored in their work include:

  • Medical Image Segmentation Techniques
  • Brain Tumor Detection and Classification
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • COVID-19 diagnosis using AI
  • Remote Sensing and LiDAR Applications

Stéphane Canu has contributed to various recent papers, reflecting an emphasis on brain tumor segmentation and image processing, among other topics. Some of the notable recent publications include:

  • "Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities," 2021, IEEE Transactions on Image Processing
  • "Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities," 2021, Neurocomputing
  • "Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation," 2020, Computerized Medical Imaging and Graphics
  • "Unsupervised damage clustering in complex aeronautical composite structures monitored by Lamb waves: An inductive approach," 2020, Engineering Applications of Artificial Intelligence
  • "Similarity Contrastive Estimation for Self-Supervised Soft Contrastive Learning," 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

The frequent co-authors collaborating with Stéphane Canu include:

  • Su Ruan
  • Samia Aïnouz
  • Tongxue Zhou
  • Pierre Véra
  • Asja Fischer

Their publications appear frequently in the following venues:

  • arXiv (Cornell University)
  • Computer Vision and Image Understanding
  • IEEE Transactions on Image Processing
  • Neurocomputing
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Stéphane Canu has also contributed to scholarly books published by Springer Science+Business Media. Several editions of the book series titled "Machine Learning and Knowledge Discovery in Databases" were published in 2023, with citation counts varying across editions.

Best Publications

  • A review: Deep learning for medical image segmentation using multi-modality fusion

    Tongxue Zhou;Tongxue Zhou;Su Ruan;Stéphane Canu

  • A review: Deep learning for medical image segmentation using multi-modality fusion

    Tongxue Zhou;Tongxue Zhou;Su Ruan;Stéphane Canu

  • More efficiency in multiple kernel learning

    Alain Rakotomamonjy;Francis Bach;Stéphane Canu;Yves Grandvalet

  • Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming

    G. Gasso;A. Rakotomamonjy;S. Canu

  • Learning with non-positive kernels

    Cheng Soon Ong;Xavier Mary;Stéphane Canu;Alexander J. Smola

  • Adaptive Scaling for Feature Selection in SVMs

    Yves Grandvalet;Stéphane Canu

  • Heteroscedastic Gaussian process regression

    Quoc V. Le;Alex J. Smola;Stéphane Canu

  • Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities

    Tongxue Zhou;Stephane Canu;Pierre Vera;Su Ruan

  • Technology and perception: the contribution of sensory substitution systems

    C. Lenay;S. Canu;P. Villon

  • Noise injection: theoretical prospects

    Yves Grandvalet;Stéphane Canu;Stéphane Boucheron

  • Environmental data mining and modeling based on machine learning algorithms and geostatistics

    Mikhail F. Kanevski;Roman Parkin;Aleksey Pozdnukhov;Aleksey Pozdnukhov;Vadim Timonin

  • Support Vector Machines with a Reject Option

    Yves Grandvalet;Alain Rakotomamonjy;Joseph Keshet;Stéphane Canu

  • Learning SVM in Kreĭn Spaces

    Gaelle Loosli;Stephane Canu;Cheng Soon Ong

  • Kernel methods and the exponential family

    Stéphane Canu;Alex Smola

  • Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM

    Lea Laporte;Remi Flamary;Stephane Canu;Sebastien Dejean

  • Frames, Reproducing Kernels, Regularization and Learning

    Alain Rakotomamonjy;Stéphane Canu

  • Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage

    Yves Grandvalet;Stéphane Canu

  • An approach to water supply clusters by semi-supervised learning

    M. Herrera;S. Canu;A. Karatzoglou;Rafael Pérez-García

  • Operator-valued kernels for learning from functional response data

    Hachem Kadri;Emmanuel Duflos;Philippe Preux;Stéphane Canu

  • $ll_{p}-ll_{q}$ Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning

    A. Rakotomamonjy;R. Flamary;G. Gasso;S. Canu

  • Automatic COVID-19 CT segmentation using U-Net integrated spatial and channel attention mechanism.

    Tongxue Zhou;Tongxue Zhou;Tongxue Zhou;Stéphane Canu;Stéphane Canu;Su Ruan;Su Ruan

  • Training Invariant SVMs Using Selective Sampling

    Léon Bottou;Olivier Chapelle;Dennis DeCoste;Jason Weston

Frequent Co-Authors

Su Ruan
Su Ruan University of Rouen
Alain Rakotomamonjy
Alain Rakotomamonjy Criteo (France)
Mikhail Kanevski
Mikhail Kanevski University of Lausanne
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Fabrice Meriaudeau
Fabrice Meriaudeau University of Franche-Comté
Christian Wolf
Christian Wolf Institut National des Sciences Appliquées de Lyon
S. V. N. Vishwanathan
S. V. N. Vishwanathan Purdue University West Lafayette
Alexandros Karatzoglou
Alexandros Karatzoglou Google (United States)
Martin T. Wells
Martin T. Wells Cornell University
Patrick C. M. Wong
Patrick C. M. Wong Chinese University of Hong Kong

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