58 citations · 59 across the 6 of their papers we have counts for
9 papers
Verification of Dynamic Holographic Behavior in Identity Documents
Glen Pouliquen, Joseph Chazalon, Guillaume Chiron +2
This paper addresses the remote verification of the authenticity of Optically Variable Devices (commonly known as holograms) on identity documents. Typically placed over the cardho…
Temporal Modeling of Optically Variable Devices in Identity Documents
Glen Pouliquen, Joseph Chazalon, Guillaume Chiron +3
Robust remote verification of identity documents relies on analyzing faint, transparent security features like Optically Variable Devices (OVDs), or "holograms", within user-captur…
Weakly Supervised Training for Hologram Verification in Identity Documents
Glen Pouliquen, Guillaume Chiron, Joseph Chazalon +2
We propose a method to remotely verify the authenticity of Optically Variable Devices (OVDs), often referred to as ``holograms'', in identity documents. Our method processes video…
Linear Object Detection in Document Images using Multiple Object Tracking
Philippe Bernet, Joseph Chazalon, Edwin Carlinet +2
Linear objects convey substantial information about document structure, but are challenging to detect accurately because of degradation (curved, erased) or decoration (doubled, das…
A Benchmark of Nested Named Entity Recognition Approaches in Historical Structured Documents
Solenn Tual, Nathalie Abadie, J Chazalon +2
Named Entity Recognition (NER) is a key step in the creation of structured data from digitised historical documents. Traditional NER approaches deal with flat named entities, where…
Entry Separation using a Mixed Visual and Textual Language Model: Application to 19th century French Trade Directories
Bertrand Duménieu, Edwin Carlinet, Nathalie Abadie +1
When extracting structured data from repetitively organized documents, such as dictionaries, directories, or even newspapers, a key challenge is to correctly segment what constitut…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
ICDAR 2021 Competition on Historical Map Segmentation
Joseph Chazalon, Edwin Carlinet, Yizi Chen +9
This paper presents the final results of the ICDAR 2021 Competition on Historical Map Segmentation (MapSeg), encouraging research on a series of historical atlases of Paris, France…
Combining Deep Learning and Mathematical Morphology for Historical Map Segmentation
Yizi Chen, Edwin Carlinet, Joseph Chazalon +3
The digitization of historical maps enables the study of ancient, fragile, unique, and hardly accessible information sources. Main map features can be retrieved and tracked through…