Document Analysis using Deep Learning Techniques

Document layout analysis is an automated process that recognizes and extracts the content and structure of various documents, including books, newspapers, and forms, using computer vision and machine learning techniques. Its main purpose is to enable accurate and efficient processing of vast amounts of digital documents in fields like digital preservation, document management, and information retrieval. Document layout analysis is widely applicable and can help with tasks such as data extraction, document classification, and information retrieval, which makes it an essential component of many modern information processing systems. This implements the layout parser and CNN architecture. The layout parser is a Python library wherein the library contains all the algorithms like R-CNN, CNN, and Faster-CNN. CNN is used to classify different components of the document based on their position in the layout, Spacy is used to extract the document and perform the natural processing tasks on the extracted text. The result is a structured representation of the layout and contents of a document that can be used for better document understanding, and information retrieval.