相关实验视频

Updated: Jan 9, 2026

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

机器学习在食品安全风险评估中的应用

Qingchuan Zhang¹, Zhe Lu¹, Zhenqiao Liu¹

¹National Engineering Research Center for Agri-Product Quality Traceability, Beijing Technology and Business University, No. 11 and No. 33 Fucheng Road, Haidian District, Beijing 100048, China.

Foods (Basel, Switzerland)

|December 11, 2025

概括

机器学习 (ML) 和深度学习 (DL) 正通过分析复杂的数据来检测污染来彻底改变食品安全. 未来的研究应该专注于可解释的模型,并将这些技术集成到危险分析和关键控制点 (HACCP) 系统中.

科学领域:

食品科学食品科学食品科学
计算机科学计算机科学
数据科学数据科学数据科学

背景情况:

供应链的全球化增加了食品安全的复杂性.
需要先进的风险评估方法.
机器学习 (ML) 和深度学习 (DL) 提供了潜在的解决方案.

研究的目的:

审查ML和DL在智能食品安全管理中的作用.
总结一下最近ML和DL应用在食品安全方面的进展.
确定未来的研究方向.

主要方法:

对食品安全中的ML和DL应用进行系统审查.
专注于生物毒素检测,重金属污染,农药/兽药残留物和微生物风险预测.
分析传统算法 (SVM,随机森林) 和无监督方法 (K-means,等级集群).
评估深度学习架构 (CNN,RNN,变压器).

主要成果:

传统的ML算法在分类和风险评估方面表现强.
无监督的方法有助于在未标记的数据中识别模式.
深度学习架构通过自动化特征提取和多模式数据集成来提高检测准确性和效率.

结论:

ML和DL对于智能食品安全管理具有变革性.
未来的工作应该优先考虑模型解释性和多模式数据融合.
建议将其集成到危险分析和关键控制点 (HACCP) 系统中,以实现实时管理.

关键词:

深度学习是一种深度学习.食品安全食品安全全球化全球化的全球化.机器学习是机器学习.

更多相关视频

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

相关概念视频

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Microorganisms in Agriculture and Food industry

Microorganisms in Agriculture and Food industry

Microorganisms play a crucial role in agriculture and the food industry, contributing to soil fertility, crop protection, and food production. Their functions range from nitrogen fixation and biopesticide production to fermentation and food preservation, making them indispensable to sustainable farming and food safety.Role in AgricultureNitrogen-fixing bacteria, such as Rhizobium (symbiotic) and Azotobacter (free-living), convert atmospheric nitrogen into ammonia through biological nitrogen...