研究使用计算机视觉和人工智能在咖啡烤中的活性食品加工技术
Youngjin Kim1, Jooho Lee1, Sangoh Kim1
1Department of Plant and Food Engineering, Sangmyung University, Sangmyeongdae-gil 31, Dongnam-gu, Cheonan, Chungcheongnam-do 31066 Republic of Korea.
Food science and biotechnology
|August 15, 2024
概括
这项研究引入了一种人工智能驱动的计算机视觉系统,用于在烤过程中实时分类咖啡豆. 咖啡豆分类模型 (CBCM) 准确识别咖啡豆,优化复杂的食品加工环境中的质量控制.
科学领域:
- 食品科学与技术 食品科学与技术
- 人工智能在制造业中的应用
- 计算机视觉应用程序 计算机视觉应用
背景情况:
- 现代食品加工需要先进的质量控制方法.
- 整合人工智能 (AI) 和计算机视觉为复杂的处理环境提供了解决方案.
- 实时监控对于优化粮食生产至关重要.
研究的目的:
- 开发和评估基于人工智能的计算机视觉系统,用于在烤过程中对咖啡豆进行分类.
- 评估机器学习 (ML) 模型在障碍物中识别咖啡豆的性能.
- 为了能够对咖啡豆在过程中的颜色变化进行定量分析.
主要方法:
- 使用机器学习 (ML) 开发咖啡豆分类模型 (CBCM).
- 实现一个集成深度学习 (DL) 技术的计算机视觉系统.
- 在模拟的旋转烤机环境中测试模型的准确性和损失.
主要成果:
- CBCM实现了最大的验证准确率为98.44%,最小的验证损失为5.40%.
- 在测试数据集上,CBCM表现出高精度 (99.27%) 和低损失 (2.82%).
- 该系统成功地量化了咖啡豆在烤过程中的颜色变化,即使存在障碍.
结论:
- 开发的AI驱动的计算机视觉解决方案有效地将咖啡豆分类到复杂的烤环境中.
- 在咖啡加工中,CBCM显示出高准确度和可靠性,用于咖啡加工的质量控制.
- 这项技术可以精确监控和优化咖啡过程.
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