For OCR recognition of complex documents (e.g. academic papers, contracts, etc.), AI Express provides the following optimization solutions:
- Preferred MinerU model: The model recognizes tables/formulas with an accuracy of 95%, has a built-in academic thesaurus, and supports multi-column typographic parsing
- Preprocessing documents: Ensure that PDF/image resolution ≥ 300dpi, less background interference; more than 50MB file is recommended to split processing
- Model Comparison Test: Registered users can run PP-StructureV3 (good at charting) and Dolphin (multimodal analysis) at the same time to compare results.
- Post-inspection mechanism: Use the system's original text-results cross-checking function, focusing on checking the inclusion of unusual mathematical symbols/table borders.
- API Optimization Solution: The developer can add a new version by appending
?post_process=trueParameter Enable Intelligent Correction Algorithm
This answer comes from the articleAI Fast Station: document parsing tool for comparing OCR models in one clickThe
May not be reproduced without permission:AI productivity tools " Practical methods to improve the accuracy of complex document OCR recognition
English 
简体中文 
日本語 
Deutsch 
Português do Brasil