As financial document automation becomes more general, table detection is receiving more
and more attention as an important part of document automation. Disclosure documents …

Table detection and structure recognition is an important component of document analysis
systems. Deep learning-based transformer models have recently demonstrated significant …

Table recognition is using the computer to automatically understand the table, to detect the
position of the table from the document or picture, and to correctly extract and identify the …

In this study, machine learning (ML) algorithms were employed to predict the pseudo-1st-
order reaction rate constants for the sonochemical degradation of aqueous organic …

Modern natural language processing (NLP) techniques increasingly require substantial
amounts of data to train robust algorithms. Building such technologies for low-resource …

Tables are widely used in documents because of their compact and structured
representation of information. In particular, in scientific papers, tables can sum up novel …

To overcome the limitations and challenges of current automatic table data annotation
methods and random table data synthesis approaches, we propose a novel method for …

Graphs are a natural representation of the patterns we glimpse in the world as we perceive
it. The data as we receive it from nature is not only a set of objects but also a group of …

Prior work on constructing challenging tabular inference data centered primarily on human
annotation or automatic synthetic generation. Both techniques have their own set of issues …

Table detection and information extraction from table images has always been an arduous
task because of the wide range of table images in different images and sizes. The proposed …