Document Image Analysis

Document image analysis focuses on automatically extracting information from scanned documents, aiming to bridge the gap between human understanding and machine interpretation of visual and textual data. Current research emphasizes improving the accuracy and efficiency of tasks like document classification, layout analysis (including table recognition), and information extraction, often leveraging deep learning models such as transformers and employing techniques like multi-modal learning and retrieval-augmented generation. This field is crucial for automating tasks in various sectors, from archiving historical documents to streamlining business processes, and ongoing efforts to improve model explainability and address privacy concerns are vital for responsible deployment.