Scanned Document

Scanned document processing focuses on efficiently extracting and enhancing information from digitized paper documents. Current research emphasizes improving Optical Character Recognition (OCR) accuracy through techniques like deep learning-based super-resolution to enhance image quality, transformer networks to remove artifacts, and hybrid approaches combining deep learning with rule-based systems for tasks such as address detection. These advancements aim to improve the speed and accuracy of information extraction from scanned documents, impacting fields ranging from automated document processing in businesses to historical text analysis in archaeology. The development of large, high-quality datasets is also crucial for training and evaluating these models.