Stéphane Canu | DeepAI

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∙ 06/15/2022

Physically-admissible polarimetric data augmentation for road-scene analysis

Polarimetric imaging, along with deep learning, has shown improved perfo...

15 Cyprien Ruffino, et al. ∙

∙ 12/24/2021

A formal approach to good practices in Pseudo-Labeling for Unsupervised Domain Adaptive Re-Identification

The use of pseudo-labels prevails in order to tackle Unsupervised Domain...

0 Fabian Dubourvieux, et al. ∙

∙ 11/29/2021

Similarity Contrastive Estimation for Self-Supervised Soft Contrastive Learning

Contrastive representation learning has proven to be an effective self-s...

0 Julien Denize, et al. ∙

∙ 11/08/2021

Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities

Using multimodal Magnetic Resonance Imaging (MRI) is necessary for accur...

18 Tongxue Zhou, et al. ∙

∙ 11/02/2021

A Tri-attention Fusion Guided Multi-modal Segmentation Network

In the field of multimodal segmentation, the correlation between differe...

0 Tongxue Zhou, et al. ∙

∙ 10/15/2021

Improving Unsupervised Domain Adaptive Re-Identification via Source-Guided Selection of Pseudo-Labeling Hyperparameters

Unsupervised Domain Adaptation (UDA) for re-identification (re-ID) is a ...

0 Fabian Dubourvieux, et al. ∙

∙ 03/22/2021

Spatio-Temporal Neural Network for Fitting and Forecasting COVID-19

We established a Spatio-Temporal Neural Network, namely STNN, to forecas...

0 Yi-Shuai Niu, et al. ∙

∙ 02/05/2021

3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint

In the field of multimodal segmentation, the correlation between differe...

4 Tongxue Zhou, et al. ∙

∙ 09/20/2020

Unsupervised Domain Adaptation for Person Re-Identification through Source-Guided Pseudo-Labeling

Person Re-Identification (re-ID) aims at retrieving images of the same p...

0 Fabian Dubourvieux, et al. ∙

∙ 04/22/2020

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

Multi-modality is widely used in medical imaging, because it can provide...

0 Tongxue Zhou, et al. ∙

∙ 04/14/2020

An automatic COVID-19 CT segmentation based on U-Net with attention mechanism

The coronavirus disease (COVID-19) pandemic has led a devastating effect...

13 Tongxue Zhou, et al. ∙

∙ 04/14/2020

An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism

The coronavirus disease (COVID-19) pandemic has led to a devastating eff...

0 Tongxue Zhou, et al. ∙

∙ 03/19/2020

Brain tumor segmentation with missing modalities via latent multi-source correlation representation

Multimodal MR images can provide complementary information for accurate ...

0 Tongxue Zhou, et al. ∙

∙ 11/26/2019

Doc2Vec on the PubMed corpus: study of a new approach to generate related articles

PubMed is the biggest and most used bibliographic database worldwide, ho...

0 Emeric Dynomant, et al. ∙

∙ 10/02/2019

Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning

Object detection in road scenes is necessary to develop both autonomous ...

0 Rachel Blin, et al. ∙

∙ 07/30/2019

Kernels on fuzzy sets: an overview

This paper introduces the concept of kernels on fuzzy sets as a similari...

0 Jorge Guevara, et al. ∙

∙ 04/16/2019

Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-Agent Reinforcement Learning

Using touch devices to navigate in virtual 3D environments such as compu...

4 Quentin Debard, et al. ∙

∙ 03/05/2019

L 1-norm double backpropagation adversarial defense

Adversarial examples are a challenging open problem for deep neural netw...

0 Ismaïla Seck, et al. ∙

∙ 02/19/2018

Learning to recognize touch gestures: recurrent vs. convolutional features and dynamic sampling

We propose a fully automatic method for learning gestures on big touch d...

0 Quentin Debard, et al. ∙

∙ 09/21/2017

A First Derivative Potts Model for Segmentation and Denoising Using MILP

Unsupervised image segmentation and denoising are two fundamental tasks ...

0 Ruobing Shen, et al. ∙

∙ 09/12/2017

Une véritable approche ℓ_0 pour l'apprentissage de dictionnaire

Sparse representation learning has recently gained a great success in si...

0 Yuan Liu, et al. ∙

∙ 10/28/2015

Operator-valued Kernels for Learning from Functional Response Data

In this paper we consider the problems of supervised classification and ...

0 Hachem Kadri, et al. ∙

∙ 01/12/2013

Multiple functional regression with both discrete and continuous covariates

In this paper we present a nonparametric method for extending functional...

0 Hachem Kadri, et al. ∙

∙ 10/06/2009

Functional learning through kernels

This paper reviews the functional aspects of statistical learning theory...

0 Stéphane Canu, et al. ∙

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