10 citations · 19 across the 7 of their papers we have counts for
7 papers
Local and Global Graph Modeling with Edge-weighted Graph Attention Network for Handwritten Mathematical Expression Recognition
Yejing Xie, Richard Zanibbi, Harold Mouchère
In this paper, we present a novel approach to Handwritten Mathematical Expression Recognition (HMER) by leveraging graph-based modeling techniques. We introduce an End-to-end model…
NeuroPapyri: A Deep Attention Embedding Network for Handwritten Papyri Retrieval
Giuseppe De Gregorio, Simon Perrin, Rodrigo C. G. Pena +2
The intersection of computer vision and machine learning has emerged as a promising avenue for advancing historical research, facilitating a more profound exploration of our past.…
Handwritten Text Recognition from Crowdsourced Annotations
Solène Tarride, Tristan Faine, Mélodie Boillet +2
In this paper, we explore different ways of training a model for handwritten text recognition when multiple imperfect or noisy transcriptions are available. We consider various tra…
Model-based inexact graph matching on top of CNNs for semantic scene understanding
Jérémy Chopin, Jean-Baptiste Fasquel, Harold Mouchère +2
Deep learning based pipelines for semantic segmentation often ignore structural information available on annotated images used for training. We propose a novel post-processing modu…
Comparison of attention models and post-hoc explanation methods for embryo stage identification: a case study
Tristan Gomez, Thomas Fréour, Harold Mouchère
An important limitation to the development of AI-based solutions for In Vitro Fertilization (IVF) is the black-box nature of most state-of-the-art models, due to the complexity of…
Towards deep learning-powered IVF: A large public benchmark for morphokinetic parameter prediction
Tristan Gomez, Magalie Feyeux, Nicolas Normand +4
An important limitation to the development of Artificial Intelligence (AI)-based solutions for In Vitro Fertilization (IVF) is the absence of a public reference benchmark to train…
Metrics for saliency map evaluation of deep learning explanation methods
Tristan Gomez, Thomas Fréour, Harold Mouchère
Due to the black-box nature of deep learning models, there is a recent development of solutions for visual explanations of CNNs. Given the high cost of user studies, metrics are ne…