摘要
本文梳理了食品安全检测的内涵和人工智能的应用基础,指出当前食品安全检测存在的主要问题,并提出了基于深度学习优化检测算法精度、机器学习构建多靶标识别模型、智能传感器提升现场检测效率等应对策略。人工智能技术有望显著提升食品安全检测的灵敏度、特异性和实时性,为保障食品安全提供有力支撑。
This article combs the connotation of food safety testing and the application basis of artificial intelligence,points out the main problems existing in current food safety testing,and proposes optimization of detection algorithm accuracy based on deep learning,machine learning to build multi-target recognition models,and smart sensors to improve on-site detection efficiency and other coping strategies.Artificial intelligence technology is expected to significantly improve the sensitivity,specificity and real-time performance of food safety testing,providing strong support for ensuring food safety.
作者
邓建勇
DENG Jianyong(Liulin County Market Supervision Administration,Liulin 033300,China)
出处
《食品安全导刊》
2024年第25期158-160,共3页
China Food Safety Magazine
关键词
食品安全检测
人工智能
深度学习
food safety testing
artificial intelligence
deep learning
