摘要
为采用人工智能领域的新一代信息技术来有效提升实际业务开展的效率,达到降本增效的目的。本文对采用图像识别技术来辅助核电企业开展文档智能化应用进行研究。文章阐述了图像识别技术的概况、分析了采用图片识别技术的业务背景、项目实施的主要过程、项目实现的基本原理和典型应用场景解决方案等内容,通过对基于图像识别技术的扫描文件清晰度的自动化检测、基于光学图像文字识别技术的文件自动化拆分和比对这两个应用场景,阐述了所需要解决的问题、解决方案的原理、具体的程序功能设计方案以及最终的应用效果。根据对相关实际应用效果的评估,证明了采用图像识别技术的技术可行性,能够为文档智能化应用发挥重要的辅助作用。通过本课题的研究和实践,为基于人工智能等技术的文档信息化技术提升做出了有益的探索。
In order to apply the new generation of information technology in the field of artificial intelligence to effectively improve the efficiency of actual business development,and achieve the purpose of reducing costs and increasing efficiency.This paper studies the use of image recognition technology to assist nuclear power enterprises in the application of document intelligence.The article expounds the general situation of image recognition technology,analyzes the business background of image recognition technology,the main process of project implementation,the basic principle of project realization and the solution of typical application scenarios,Through the automatic detection of scanning file sharpness based on image recognition technology,the automatic resolution of files based on optical image text recognition technology,and the comparison of these two application scenarios,This paper expounds the problems to be solved,the principle of the solution,the specific program function design scheme and the final application effect.According to the evaluation of the relevant practical application results,it is proved that the technical feasibility of adopting image recognition technology can play an important supporting role for the intelligent application of documents.Through the research and practice of this topic,it makes a beneficial exploration for the promotion of document information technology based on artificial intelligence and other technologies.
作者
杨强
胡心宇
YANG Qiang;Hu Xinyu(Jiangsu Nuclear Power Co.,Ltd.,Lianyungang 222000 Jiangsu,China)
出处
《电力大数据》
2019年第11期58-63,共6页
Power Systems and Big Data
关键词
图像识别技术
光学图像文字识别
档案信息技术
文档信息化
信息资源利用
image recognition technology
optical image text recognition
archive information technology
document information
information resource utilization