IDTrust: Deep Identity Document Quality Detection with Bandpass Filtering

no code implementations • 1 Mar 2024 • Musab Al-Ghadi, Joris Voerman, Souhail Bakkali, Mickaël Coustaty, Nicolas Sidere, Xavier St-Georges

The increasing use of digital technologies and mobile-based registration procedures highlights the vital role of personal identity documents (IDs) in verifying users and safeguarding sensitive information.

A Comprehensive Survey of Document-level Relation Extraction (2016-2023)

no code implementations • 28 Sep 2023 • Julien Delaunay, Hanh Thi Hong Tran, Carlos-Emiliano González-Gallardo, Georgeta Bordea, Nicolas Sidere, Antoine Doucet

Document-level relation extraction (DocRE) is an active area of research in natural language processing (NLP) concerned with identifying and extracting relationships between entities beyond sentence boundaries.

Document-level Relation Extraction Relation +1

Named entity recognition architecture combining contextual and global features

1 code implementation • 15 Dec 2021 • Tran Thi Hong Hanh, Antoine Doucet, Nicolas Sidere, Jose G. Moreno, Senja Pollak

Named entity recognition (NER) is an information extraction technique that aims to locate and classify named entities (e. g., organizations, locations,...) within a document into predefined categories.

named-entity-recognition Named Entity Recognition +1

Alleviating Digitization Errors in Named Entity Recognition for Historical Documents

1 code implementation • CONLL 2020 • Emanuela Boros, Ahmed Hamdi, Elvys Linhares Pontes, Luis Adri{\'a}n Cabrera-Diego, Jose G. Moreno, Nicolas Sidere, Antoine Doucet

This paper tackles the task of named entity recognition (NER) applied to digitized historical texts obtained from processing digital images of newspapers using optical character recognition (OCR) techniques.

named-entity-recognition Named Entity Recognition +3