TableDet: An end-to-end deep learning approach for table detection and table image classification in data sheet images

J Fernandes, M Simsek, B Kantarci, S Khan - Neurocomputing, 2022 - Elsevier
Global supply chains are kept viable through the information shared through billions of
electronic documents, many of which extensively use tables to display critical information …

Intelligent document processing in end-to-end RPA contexts: a systematic literature review

A Martínez-Rojas, JM López-Carnicer… - Confluence of Artificial …, 2023 - Springer
Automating organizational processes typically involves document processing techniques for
a large document set. For that purpose, the Intelligent Document Processing (IDP) paradigm …

Tabcellnet: Deep learning-based tabular cell structure detection

JC Jiang, M Simsek, B Kantarci, S Khan - Neurocomputing, 2021 - Elsevier
There is an increasing demand for automated document processing techniques as the
volume of electronic component documents increase. This is most prevalent in the supply …

On cropped versus uncropped training sets in tabular structure detection

Y Akkaya, M Simsek, B Kantarci, S Khan - Neurocomputing, 2022 - Elsevier
Automated document processing for tabular information extraction is highly desired in many
organizations, from industry to government. Prior works addressed this problem under table …

Tabular information extraction from datasheets with deep learning for semantic modeling

Y Akkaya - 2022 - ruor.uottawa.ca
The growing popularity of artificial intelligence and machine learning has led to the adop-
tion of the automation vision in the industry by many other institutions and organizations …

High Precision Deep Learning-Based Tabular Data Extraction

JC Jiang - 2021 - ruor.uottawa.ca
The advancements of AI methodologies and computing power enables automation and
propels the Industry 4.0 phenomenon. Information and data are digitized more than ever …