OCR extraction based on power metering inspection reports technical studies

This paper discusses OCR extraction techniques based on power metering inspection reports. With the rapid development of the electric power industry, the number of power metering inspection reports continues to grow, and the traditional manual processing method faces the challenges of inefficiency and error-prone. OCR technology has become an ideal choice for solving this problem, but the complex electric power symbols and units of measurement in the power metering inspection reports have brought new challenges to OCR technology. This paper details the application and principles of Convolutional Neural Network (CNN), YOLO algorithm in OCR extraction techniques for power metering inspection reports. CNN is used for feature extraction to integrate feature extraction, sequence modeling and transcription into a unified framework, while YOLO algorithm redefines object detection as a regression problem. These algorithms provide strong support for automated and intelligent processing of power metering inspection reports, which helps to improve data processing efficiency and accuracy.