We introduce Dessurt, a relatively simple document understanding transformer capable of
being fine-tuned on a greater variety of document tasks than prior methods. It receives a …

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 …

We propose a Transformer-based approach for information extraction from digitized
handwritten documents. Our approach combines, in a single model, the different steps that …

Named entities (NEs) are fundamental in the extraction of information from text. The
recognition and classification of these entities into predefined categories is called Named …

Abstract Information extraction from handwritten documents involves traditionally three
distinct steps: Document Layout Analysis, Handwritten Text Recognition, and Named Entity …

Semantic analysis of handwritten document images offers a wide range of practical
application scenarios. A sequential combination of handwritten text recognition (HTR) and a …

Abstract Automating Information Extraction (IE) from handwritten documents is a challenging
task due to the wide variety of handwriting styles, the presence of noise, and the lack of …

A semantic analysis of documents offers a wide range of practical application scenarios.
Thereby, the combination of handwriting recognizer and textual NLP models constitutes an …

Abstract Performing Named Entity Recognition on Handwritten Documents results in
categorizing particular fragments of the automatic transcription which may be employed in …

Automated evaluation of handwritten answers has been a challenging problem for scaling
the education system for many years. Speeding up the evaluation remains as the major …