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中国精品科技期刊2020
郭兴,孙莹,刘树萍,等. 深度学习在食品质量与安全检测中的 应用进展[J]. 华体会体育,2025,46(6):1−11. doi: 10.13386/j.issn1002-0306.2024040375.
引用本文: 郭兴,孙莹,刘树萍,等. 深度学习在食品质量与安全检测中的 应用进展[J]. 华体会体育,2025,46(6):1−11. doi: 10.13386/j.issn1002-0306.2024040375.
GUO Xing, SUN Ying, LIU Shuping, et al. Advance in Application of Deep Learning in Food Quality and Safety Detection[J]. Science and Technology of Food Industry, 2025, 46(6): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024040375.
Citation: GUO Xing, SUN Ying, LIU Shuping, et al. Advance in Application of Deep Learning in Food Quality and Safety Detection[J]. Science and Technology of Food Industry, 2025, 46(6): 1−11. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2024040375.

深度学习在食品质量与安全检测中的 应用进展

Advance in Application of Deep Learning in Food Quality and Safety Detection

  • 摘要: 随着人们生活水平的提高,消费者对食品质量与安全的需求日益增长。传统检测食品质量与安全的方法已经无法满足人们对高效、准确和可靠检测的需求。因此,寻求一种更高效、便捷的检测方法成为当务之急。在此基础上,基于深度神经网络的机器学习技术即深度学习的快速发展为食品质量与安全检测带来了新的契机。本文围绕深度学习在食品质量与安全检测中的应用进展,介绍了传统机器学习和深度学习的原理,阐述深度学习在食品原产地追溯以及食品品质中对食品缺陷、新鲜度、掺假和病原体等检测中的应用,并对深度学习在食品质量与安全检测领域的发展趋势进行了展望,以期为食品质量与安全检测领域提供理论参考和研究思路。

     

    Abstract: With the improvement of people's living standards, consumers' demand for food quality and safety is growing. Traditional methods for detecting food quality and safety can no longer meet the demand for efficient, accurate and reliable detection. Therefore, it becomes imperative to seek a more efficient and convenient detection method. On this basis, the rapid development of deep neural network-based machine learning technology, i.e., deep learning, has brought new opportunities for food quality and safety detection. This paper focuses on the progress of the application of deep learning in food quality and safety inspection, introduces the principles of traditional machine learning and deep learning, describes the application of deep learning in the traceability of food origin and the detection of food defects, freshness, adulteration and pathogens in food quality, and looks forward to the development trend of the development trend of deep learning in the field of food quality and safety inspection with a view to providing theoretical references for the food quality and safety inspection field by providing theoretical references and research ideas.

     

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