Digital construction of data traceability based on dynamic recognition algorithm

Abstract

Traceability result confirmation is an important link to ensure the accuracy and reliability of the standard measurement value. At present, the corresponding certificates/reports issued by superior technical institutions are not digital information, which requires manual comparison of relevant data, resulting in low efficiency and high error rate. Combined with deep learning theory, this paper proposes a dynamic recognition algorithm which can be applied to image, text and other information carriers to realize intelligent recognition of images, symbols and digital content. Based on this algorithm, a digital system for quantitative traceability is developed, and a set of intelligent data extraction, error correction and structured platform is built to improve the efficiency and accuracy of metrological verification.