Table Detection & Data Extraction from Documents using Object Detection

Table detection and data extraction from documents is a crucial task in the field of computer vision and document analysis. The goal is to automatically detect tables in documents and extract relevant information from them. This can be achieved through object detection techniques, which use machine learning algorithms to identify objects in images and extract information from them. The process involves training a model on a dataset of table images, and then using the trained model to detect tables in new images. Once tables are detected, data extraction algorithms can be used to extract text and numerical information from the cells of the table. This information can then be used for a variety of applications, such as database creation, business intelligence, and data analysis.