一种基于深度学习的OCR技术神经网络模型系统
By designing a neural network model system for OCR technology, and using techniques such as convolutional neural networks to generate and verify consistent text information, the problem of inconsistent text recognition in existing OCR methods is solved, thereby improving recognition accuracy and processing speed.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGDONG CHAOTING GRP CO LTD
- Filing Date
- 2023-03-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing deep learning-based OCR methods suffer from inconsistencies when recognizing multiple candidate texts, leading to a decrease in processing speed.
Design a neural network model system for OCR technology based on deep learning, including modules for image acquisition, processing, conversion, verification, and storage. It recognizes text through convolutional neural networks, recurrent neural networks, and long short-term memory networks, and generates text information consistent with the original image. The image verification module is used to improve the recognition accuracy.
By combining the cropping and verification modules, the accuracy and processing speed of text recognition are improved, and the need for repeated recognition is reduced.
Smart Images
Figure CN116343220B_ABST