Isabelle Bloch

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Featured Co-authors

Ya Zhang
123 publications
Stephan Clémençon
56 publications
Andrei Bursuc
34 publications
Céline Hudelot
31 publications
Pietro Gori
29 publications
Jerome Lang
28 publications
Jamal Atif
28 publications
Florian Yger
23 publications
Pavlo Mozharovskyi
20 publications
Rozenn Dahyot
19 publications
Jesús Angulo
19 publications

research

∙ 08/22/2023

Non-Redundant Combination of Hand-Crafted and Deep Learning Radiomics: Application to the Early Detection of Pancreatic Cancer

We address the problem of learning Deep Learning Radiomics (DLR) that ar...

0 Rebeca Vétil, et al. ∙

research

∙ 08/18/2023

Decoupled conditional contrastive learning with variable metadata for prostate lesion detection

Early diagnosis of prostate cancer is crucial for efficient treatment. M...

0 Camille Ruppli, et al. ∙

research

∙ 07/10/2023

Weakly-supervised positional contrastive learning: application to cirrhosis classification

Large medical imaging datasets can be cheaply and quickly annotated with...

0 Emma Sarfati, et al. ∙

research

∙ 05/11/2023

Meta-Learners for Few-Shot Weakly-Supervised Medical Image Segmentation

Most uses of Meta-Learning in visual recognition are very often applied ...

0 Hugo Oliveira, et al. ∙

research

∙ 03/08/2023

Morpho-logic from a Topos Perspective: Application to symbolic AI

Modal logics have proved useful for many reasoning tasks in symbolic art...

0 Marc Aiguier, et al. ∙

research

∙ 02/16/2023

Learning to diagnose cirrhosis from radiological and histological labels with joint self and weakly-supervised pretraining strategies

Identifying cirrhosis is key to correctly assess the health of the liver...

0 Emma Sarfati, et al. ∙

research

∙ 01/18/2023

Model-based inexact graph matching on top of CNNs for semantic scene understanding

Deep learning based pipelines for semantic segmentation often ignore str...

0 Jérémy Chopin, et al. ∙

research

∙ 10/21/2022

Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection

We propose a scalable and data-driven approach to learn shape distributi...

0 Rebeca Vétil, et al. ∙

research

∙ 10/04/2022

Anatomically constrained CT image translation for heterogeneous blood vessel segmentation

Anatomical structures such as blood vessels in contrast-enhanced CT (ceC...

0 Giammarco La Barbera, et al. ∙

research

∙ 07/27/2022

Optimizing transformations for contrastive learning in a differentiable framework

Current contrastive learning methods use random transformations sampled ...

0 Camille Ruppli, et al. ∙

research

∙ 07/06/2022

Is the U-Net Directional-Relationship Aware?

CNNs are often assumed to be capable of using contextual information abo...

0 Mateus Riva, et al. ∙

research

∙ 05/12/2022

Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers

Augmented reality applications have rapidly spread across online platfor...

8 Robin Kips, et al. ∙

research

∙ 02/08/2022

Hair Color Digitization through Imaging and Deep Inverse Graphics

Hair appearance is a complex phenomenon due to hair geometry and how the...

15 Robin Kips, et al. ∙

research

∙ 02/01/2022

A deep residual learning implementation of Metamorphosis

In medical imaging, most of the image registration methods implicitly as...

0 Matthis Maillard, et al. ∙

research

∙ 07/06/2021

Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation

Due to a high heterogeneity in pose and size and to a limited number of ...

0 Giammarco La Barbera, et al. ∙

research

∙ 07/05/2021

Template-Based Graph Clustering

We propose a novel graph clustering method guided by additional informat...

0 Mateus Riva, et al. ∙

research

∙ 06/17/2021

Knowledge distillation from multi-modal to mono-modal segmentation networks

The joint use of multiple imaging modalities for medical image segmentat...

0 Minhao Hu, et al. ∙

research

∙ 05/12/2021

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

While makeup virtual-try-on is now widespread, parametrizing a computer ...

17 Robin Kips, et al. ∙

research

∙ 02/22/2021

Approximation of dilation-based spatial relations to add structural constraints in neural networks

Spatial relations between objects in an image have proved useful for str...

0 Mateus Riva, et al. ∙

research

∙ 01/18/2021

Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI

We address the problem of multimodal liver segmentation in paired but un...

0 Vincent Couteaux, et al. ∙

research

∙ 12/04/2020

Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification

Bayesian neural networks (BNNs) have been long considered an ideal, yet ...

1 Gianni Franchi, et al. ∙

research

∙ 09/29/2020

Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations

Deep learning methods are widely used for medical applications to assist...

0 Antoine Pirovano, et al. ∙

research

∙ 08/24/2020

CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

While existing makeup style transfer models perform an image synthesis w...

8 Robin Kips, et al. ∙

research

∙ 06/01/2020

One Versus all for deep Neural Network Incertitude (OVNNI) quantification

Deep neural networks (DNNs) are powerful learning models yet their resul...

22 Gianni Franchi, et al. ∙

research

∙ 05/04/2020

Abstract Mathematical morphology based on structuring element: Application to morpho-logic

A general definition of mathematical morphology has been defined within ...

0 Marc Aiguier, et al. ∙

research

∙ 03/13/2020

Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach

The recent enthusiasm for artificial intelligence (AI) is due principall...

0 Valérie Beaudouin, et al. ∙

research

∙ 12/24/2019

TRADI: Tracking deep neural network weight distributions

During training, the weights of a Deep Neural Network (DNN) are optimize...

19 Gianni Franchi, et al. ∙

research

∙ 03/20/2019

Part-based approximations for morphological operators using asymmetric auto-encoders

This paper addresses the issue of building a part-based representation o...

0 Bastien Ponchon, et al. ∙

research

∙ 03/19/2019

Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks

Following recent advances in morphological neural networks, we propose t...

0 Yunxiang Zhang, et al. ∙

research

∙ 03/05/2018

Explanatory relations in arbitrary logics based on satisfaction systems, cutting and retraction

The aim of this paper is to introduce a new framework for defining abduc...

0 Marc Aiguier, et al. ∙

research

∙ 02/14/2018

Morphologic for knowledge dynamics: revision, fusion, abduction

Several tasks in artificial intelligence require to be able to find mode...

0 Isabelle Bloch, et al. ∙

research

∙ 10/16/2017

Dual Logic Concepts based on Mathematical Morphology in Stratified Institutions: Applications to Spatial Reasoning

Several logical operators are defined as dual pairs, in different types ...

0 Marc Aiguier, et al. ∙

research

∙ 01/16/2017

Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection

The classification of MRI images according to the anatomical field of vi...

0 Hadrien Bertrand, et al. ∙

research

∙ 12/19/2016

Exploring Structure for Long-Term Tracking of Multiple Objects in Sports Videos

In this paper, we propose a novel approach for exploiting structural rel...

0 Henrique Morimitsu, et al. ∙

research

∙ 02/26/2015

Relaxation-based revision operators in description logics

As ontologies and description logics (DLs) reach out to a broader audien...

0 Marc Aiguier, et al. ∙

research

∙ 05/13/2008

A New Algorithm for Interactive Structural Image Segmentation

This paper proposes a novel algorithm for the problem of structural imag...

0 Alexandre Noma, et al. ∙

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