In this survey, we provide a comprehensive review of more than 200 articles, technical
reports, and GitHub repositories published over the last 10 years on the recent …

The first phase of table recognition is to detect the tabular area in a document.
Subsequently, the tabular structures are recognized in the second phase in order to extract …

This paper presents a novel end-to-end system for table understanding in document images
called DeepDeSRT. In particular, the contribution of DeepDeSRT is two-fold. First, it …

This paper presents a novel approach for the detection of tables present in documents,
leveraging the potential of deep neural networks. Conventional approaches for table …

Automatic information extraction from online published scientific documents is useful in
various applications such as tagging, web indexing and search engine optimization. As a …

In the Fourth Industrial Revolution, artificial intelligence technology and big data science are
emerging rapidly. To apply these informational technologies to the engineering industries, it …

Tabular data is a crucial form of information expression, which can organize data in a
standard structure for easy information retrieval and comparison. However, in financial …

We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of
figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis …

This paper presents the novel approach towards table structure recognition by leveraging
the guided anchors. The concept differs from current state-of-the-art systems for table …

Identifying and extracting figures and tables along with their captions from scholarly articles
is important both as a way of providing tools for article summarization, and as part of larger …