Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Unlock the full potential of AI with Building LLMs for Productionβ€”our 470+ page guide to mastering LLMs with practical projects and expert insights!

Publication

Unlocking Key Technologies in Document Parsing
Latest   Machine Learning

Unlocking Key Technologies in Document Parsing

Last Updated on November 7, 2024 by Editorial Team

Author(s): Florian June

Originally published on Towards AI.

A Comprehensive Guide with Insights

This member-only story is on us. Upgrade to access all of Medium.

A large number of documents β€” including technical documentation, historical records, academic publications, and legal files β€” exist in scanned or image formats. This presents significant challenges for downstream tasks like Retrieval-Augmented Generation (RAG), information extraction, and document understanding.

Document parsing addresses these challenges by identifying and extracting various elements like text, equations, tables, and images from diverse documents while preserving their structural relationships. The extracted content is then converted into structured formats such as Markdown, HTML, or JSON, enabling seamless integration with downstream tasks.

In previous articles, we have shared numerous technologies related to intelligent document parsing. This article reviews and summarizes these technologies from my previous writings and two novel surveys, concluding with my personal thoughts and insights.

Figure 1: Overview of document parsing methodology. Source: Document Parsing Unveiled.

Document parsing can be broadly categorized into two methodologies: the modular pipeline system and the end-to-end approach based on large vision-language models.

Figure 2: Two methodology of document parsing. Source: Document Parsing Unveiled.

Modular pipeline system breaks down document parsing into separate stages, each focusing on specific tasks and features. The modules are typically as follows:

Layout Analysis: Detects document structure by identifying elements like… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.

Published via Towards AI

Feedback ↓