1 code implementation • 11 Mar 2019 • Bastien Moysset, Ronaldo Messina
Modern handwritten text recognition techniques employ deep recurrent neural networks.
1 code implementation • 1 Mar 2019 • Eloi Alonso, Bastien Moysset, Ronaldo Messina
State-of-the-art offline handwriting text recognition systems tend to use neural networks and therefore require a large amount of annotated data to be trained.
no code implementations • 27 Nov 2018 • Bastien Moysset, Ronaldo Messina
In this work, we aim at a fair comparison between 2D and competing models and also extensively evaluate them on more complex datasets that are more representative of challenging "real-world" data, compared to "academic" datasets that are more restricted in their complexity.
no code implementations • 27 Apr 2017 • Bastien Moysset, Christopher Kermorvant, Christian Wolf
Text line detection and localization is a crucial step for full page document analysis, but still suffers from heterogeneity of real life documents.
no code implementations • 17 Nov 2016 • Bastien Moysset, Christoper Kermorvant, Christian Wolf
The current trend in object detection and localization is to learn predictions with high capacity deep neural networks trained on a very large amount of annotated data and using a high amount of processing power.