Optical Character Recognition
Optical Character Recognition (OCR) is the automated process of converting images of text—such as scanned documents or photos—into machine-encoded, editable, and searchable data.
Specialized Models & Emerging Trends
- Nanonets OCR Small: A newly introduced, highly efficient model featuring 3B parameters, specifically optimized for converting tables into text to support Retrieval-Augmented Generation (RAG) workflows.
- Shift Toward Efficiency: There is a growing industry trend toward smaller, specialized, and high-performance models, contrasting with larger-scale architectures such as Llama OCR and Mistral OCR.
- Infographic Text Correction: Utilizing Adobe Acrobat and Canva (‘Grab Text’) to identify and correct spelling inaccuracies or errors within
- Local LLM Integration: Recent developments highlight the feasibility of building privacy-focused desktop applications using locally run Large Language Models and coding agents, eliminating dependency on cloud-based services for text extraction and processing Local LLM-Powered Privacy-Focused OCR App Development Summary Report.