no code implementations • COLING (LaTeCHCLfL, CLFL, LaTeCH) 2020 • Herve Dejean, Jean-Luc Meunier
We present Vital Records, a demonstrator based on deep-learning approaches to handwritten-text recognition, table processing and information extraction, which enables data from century-old documents to be parsed and analysed, making it possible to explore death records in space and time.
no code implementations • 9 May 2022 • Hervé Déjean, Stéphane Clinchant, Jean-Luc Meunier
This paper investigates the Relation Extraction task in documents by benchmarking two different neural network models: a multi-modal language model (LayoutXLM) and a Graph Neural Network: Edge Convolution Network (ECN).
no code implementations • WS 2019 • Alexandre Bérard, Ioan Calapodescu, Marc Dymetman, Claude Roux, Jean-Luc Meunier, Vassilina Nikoulina
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe. naverlabs. com/research/natural-language-processing/machine-translation-of-restaurant-reviews), and define a new task to encourage research on Neural Machine Translation robustness and domain adaptation, in a real-world scenario where better-quality MT would be greatly beneficial.
no code implementations • 14 Jun 2019 • Stéphane Clinchant, Hervé Déjean, Jean-Luc Meunier, Eva Lang, Florian Kleber
We present in this paper experiments on Table Recognition in hand-written registry books.
no code implementations • 17 Jul 2018 • Animesh Prasad, Hervé Déjean, Jean-Luc Meunier, Max Weidemann, Johannes Michael, Gundram Leifert
In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robust reading competition.
no code implementations • 25 Aug 2017 • Jean-Luc Meunier
This paper is concerned with structured machine learning, in a supervised machine learning context.