arXiv:2210.04716
A two-stage approach for table extraction in invoices
원문 초록
The automated analysis of administrative documents is an important field in document recognition that is studied for decades. Invoices are key documents among these huge amounts of documents available in companies and public services. Invoices contain most of the time data that are presented in tables that should be clearly identified to extract suitable information. In this paper, we propose an approach that combines an image processing based estimation of the shape of the tables with a graph-based representation of the document, which is used to identify complex tables precisely. We propose an experimental evaluation using a real case application.
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QUEST: Quality-aware Semi-supervised Table Extraction for Business Documents
SynFinTabs: A Dataset of Synthetic Financial Tables for Information and Table Extraction
PdfTable: A Unified Toolkit for Deep Learning-Based Table Extraction
H-STAR: LLM-driven Hybrid SQL-Text Adaptive Reasoning on Tables
SIMPLOT: Enhancing Chart Question Answering by Distilling Essentials
Schema-Driven Information Extraction from Heterogeneous Tables
토론
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