财务表格提取图像文档

W. Watson, Bo Liu
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引用次数: 0

摘要

长期以来,表提取一直是金融服务中普遍存在的问题。这在图像领域更具挑战性,因为内容被锁定在繁琐的像素格式后面。幸运的是,深度学习在图像分割、OCR和序列建模方面的进步为实现令人印象深刻的结果提供了必要的提升。本文提出了一种端到端的管道,用于识别、提取和转录图像文档中的表格内容,同时高保真地保留原始空间关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Financial table extraction in image documents
Table extraction has long been a pervasive problem in financial services. This is more challenging in the image domain, where content is locked behind cumbersome pixel format. Luckily, advances in deep learning for image segmentation, OCR, and sequence modeling provides the necessary heavy lifting to achieve impressive results. This paper presents an end-to-end pipeline for identifying, extracting and transcribing tabular content in image documents, while retaining the original spatial relations with high fidelity.
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