63 citations · 101 across the 11 of their papers we have counts for
12 papers · 1 filter
I Can't Believe It's Not Better: In-air Movement For Alzheimer Handwriting Synthetic Generation
Asma Bensalah, Antonio Parziale, Giuseppe De Gregorio +3
During recent years, there here has been a boom in terms of deep learning use for handwriting analysis and recognition. One main application for handwriting analysis is early detec…
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts
Giuseppe De Gregorio, Sanket Biswas, Mohamed Ali Souibgui +4
Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available…
Text-DIAE: A Self-Supervised Degradation Invariant Autoencoders for Text Recognition and Document Enhancement
Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla +6
In this paper, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE), a self-supervised model designed to tackle two tasks, text recognition (handwritten or scene-text)…
DocEnTr: An End-to-End Document Image Enhancement Transformer
Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni +4
Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for…
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement
Sana Khamekhem Jemni, Mohamed Ali Souibgui, Yousri Kessentini +1
Handwritten document images can be highly affected by degradation for different reasons: Paper ageing, daily-life scenarios (wrinkles, dust, etc.), bad scanning process and so on.…
One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
Mohamed Ali Souibgui, Ali Furkan Biten, Sounak Dey +5
Low resource Handwritten Text Recognition (HTR) is a hard problem due to the scarce annotated data and the very limited linguistic information (dictionaries and language models). F…
A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition
Mohamed Ali Souibgui, Alicia Fornés, Yousri Kessentini +1
Encoded (or ciphered) manuscripts are a special type of historical documents that contain encrypted text. The automatic recognition of this kind of documents is challenging because…
Learning Graph Edit Distance by Graph Neural Networks
Pau Riba, Andreas Fischer, Josep Lladós +1
The emergence of geometric deep learning as a novel framework to deal with graph-based representations has faded away traditional approaches in favor of completely new methodologie…
Pay Attention to What You Read: Non-recurrent Handwritten Text-Line Recognition
Lei Kang, Pau Riba, Marçal Rusiñol +2
The advent of recurrent neural networks for handwriting recognition marked an important milestone reaching impressive recognition accuracies despite the great variability that we o…
GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images
Lei Kang, Pau Riba, Yaxing Wang +3
Although current image generation methods have reached impressive quality levels, they are still unable to produce plausible yet diverse images of handwritten words. On the contrar…
Candidate Fusion: Integrating Language Modelling into a Sequence-to-Sequence Handwritten Word Recognition Architecture
Lei Kang, Pau Riba, Mauricio Villegas +2
Sequence-to-sequence models have recently become very popular for tackling handwritten word recognition problems. However, how to effectively integrate an external language model i…
A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages
Manuel Carbonell, Alicia Fornés, Mauricio Villegas +1
In the last years, the consolidation of deep neural network architectures for information extraction in document images has brought big improvements in the performance of each of t…