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计算机视觉和深度学习在粮油及其制品无损检测中的应用

张书鸣 王欣 谈文娇 郑玲春 许桐 王强

食品科学2025,Vol.46Issue(22):40-49,10.
食品科学2025,Vol.46Issue(22):40-49,10.DOI:10.7506/spkx1002-6630-20250520-133

计算机视觉和深度学习在粮油及其制品无损检测中的应用

Application of Computer Vision and Deep Learning in Non-destructive Testing of Grains,Oils and Their Products

张书鸣 1王欣 2谈文娇 2郑玲春 2许桐 2王强3

作者信息

  • 1. 重庆第二师范学院生物与化学工程学院,重庆 400067||重庆第二师范学院 油脂资源利用与创新重庆市工程研究中心,重庆 400067
  • 2. 重庆第二师范学院生物与化学工程学院,重庆 400067
  • 3. 重庆第二师范学院生物与化学工程学院,重庆 400067||重庆第二师范学院 油脂资源利用与创新重庆市工程研究中心,重庆 400067||重庆第二师范学院 熊猫学院,重庆 400067
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摘要

Abstract

Grain and oil safety is one of the important food safety issues and has received widespread attention worldwide.Therefore,rapid,accurate and efficient detection technologies are crucial for ensuring the safety of grains and oils.However,traditional detection methods for grains and oils have disadvantages such as long-time consumption,large subjective errors and poor real-time performance,which cannot meet consumers'high requirements for food quality.The combination of computer vision and deep learning provides a rapid,efficient and non-destructive solution for grain and oil detection.This article introduces the basic principles of deep learning and computer vision and their advantages in food detection,focusing on the application of algorithms such as convolutional neural network(CNN),long short-term memory(LSTM),and generative adversarial network(GAN)in grain and oil detection.Meanwhile,it demonstrates the significant effects of these technologies in improving the detection accuracy and efficiency and summarizes recent progress in the application of computer vision and deep learning in non-destructive testing of grains,oils and their products.Finally,the limitations and future trends of computer vision and deep learning in the field of grain and oil safety are discussed from various aspects such as optimizing the robustness and interpretability of the model and developing lightweight models to adapt to the resource-constrained detection environment,aiming to promote the development of more efficient and accurate food detection technologies.

关键词

计算机视觉/深度学习/粮油/无损检测

Key words

computer vision/deep learning/grains and oils/non-destructive testing

分类

轻工业

引用本文复制引用

张书鸣,王欣,谈文娇,郑玲春,许桐,王强..计算机视觉和深度学习在粮油及其制品无损检测中的应用[J].食品科学,2025,46(22):40-49,10.

基金项目

重庆市企业科技攻关联合行动计划项目(CSTB2025TIAD-qykjggX0275) (CSTB2025TIAD-qykjggX0275)

重庆市自然科学基金创新发展联合基金项目(CSTB2025NSCQ-LZX0127) (CSTB2025NSCQ-LZX0127)

重庆第二师范学院2025年度科技创新项目定向计划-前沿交叉研究基金项目(2025XJQYJCYJ03) (2025XJQYJCYJ03)

食品科学

OA北大核心

1002-6630

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