Advancements and challenges in handwritten text recognition: A comprehensive survey
Handwritten Text Recognition (HTR) is essential for digitizing historical documents in
different kinds of archives. In this study, we introduce a hybrid form archive written in French …
different kinds of archives. In this study, we introduce a hybrid form archive written in French …
Transformer-based approach for joint handwriting and named entity recognition in historical document
The extraction of relevant information carried out by named entities in handwriting
documents is still a challenging task. Unlike traditional information extraction approaches …
documents is still a challenging task. Unlike traditional information extraction approaches …
Neural models for semantic analysis of handwritten document images
O Tüselmann, GA Fink - International Journal on Document Analysis and …, 2024 - Springer
Semantic analysis of handwritten document images offers a wide range of practical
application scenarios. A sequential combination of handwritten text recognition (HTR) and a …
application scenarios. A sequential combination of handwritten text recognition (HTR) and a …
Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents
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 …
task due to the wide variety of handwriting styles, the presence of noise, and the lack of …
FATURA: A Multi-Layout Invoice Image Dataset for Document Analysis and Understanding
M Limam, M Dhiaf, Y Kessentini - arXiv preprint arXiv:2311.11856, 2023 - arxiv.org
Document analysis and understanding models often require extensive annotated data to be
trained. However, various document-related tasks extend beyond mere text transcription …
trained. However, various document-related tasks extend beyond mere text transcription …
Information Extraction from Multi-Layout Invoice Images using FATURA Dataset
M Limam, M Dhiaf, Y Kessentini - 2023 - researchsquare.com
Document analysis and understanding models often require extensive annotated data to be
trained. However, various document-related tasks extend beyond mere text transcription …
trained. However, various document-related tasks extend beyond mere text transcription …
[PDF][PDF] Open-Source Large Language Models Excel in Named Entity Recognition
D Zhu, S Li, N Thompson, KW Wong - nikthompson.com
Current state-of-the-art Named Entity Recognition (NER) typically involves fine-tuning
transformer-based models like BERT or RoBERTa with annotated datasets, posing …
transformer-based models like BERT or RoBERTa with annotated datasets, posing …
[引用][C] Neuronale Ansätze zur semantischen Analyse handschriftlicher Dokumentenbilder
O Tüselmann - Dissertation, Dortmund, Technische …