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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...
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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...
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07/10/2023
Weakly-supervised positional contrastive learning: application to cirrhosis classification
Large medical imaging datasets can be cheaply and quickly annotated with...
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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 ...
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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...
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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...
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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...
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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...
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10/04/2022
Anatomically constrained CT image translation for heterogeneous blood vessel segmentation
Anatomical structures such as blood vessels in contrast-enhanced CT (ceC...
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07/27/2022
Optimizing transformations for contrastive learning in a differentiable framework
Current contrastive learning methods use random transformations sampled ...
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07/06/2022
Is the U-Net Directional-Relationship Aware?
CNNs are often assumed to be capable of using contextual information abo...
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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...
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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...
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02/01/2022
A deep residual learning implementation of Metamorphosis
In medical imaging, most of the image registration methods implicitly as...
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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 ...
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07/05/2021
Template-Based Graph Clustering
We propose a novel graph clustering method guided by additional informat...
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06/17/2021
Knowledge distillation from multi-modal to mono-modal segmentation networks
The joint use of multiple imaging modalities for medical image segmentat...
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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 ...
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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...
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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...
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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 ...
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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...
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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...
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06/01/2020
One Versus all for deep Neural Network Incertitude (OVNNI) quantification
Deep neural networks (DNNs) are powerful learning models yet their resul...
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05/04/2020
Abstract Mathematical morphology based on structuring element: Application to morpho-logic
A general definition of mathematical morphology has been defined within ...
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03/13/2020
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach
The recent enthusiasm for artificial intelligence (AI) is due principall...
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12/24/2019
TRADI: Tracking deep neural network weight distributions
During training, the weights of a Deep Neural Network (DNN) are optimize...
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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...
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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...
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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...
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02/14/2018
Morphologic for knowledge dynamics: revision, fusion, abduction
Several tasks in artificial intelligence require to be able to find mode...
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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 ...
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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...
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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...
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02/26/2015
Relaxation-based revision operators in description logics
As ontologies and description logics (DLs) reach out to a broader audien...
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05/13/2008