计算机视觉与人工智能用于快速,低成本,环保和准确的预测酒风格和品牌
João Victor de Sousa Dutra1, Maiara Oliveira Salles1, Ricardo Cunha Michel1
1Universidade Federal do Rio de Janeiro, Avenida Athos da Silveira Ramos, Rio de Janeiro, 21491-909, Brazil. daniellavale@iq.ufrj.br.
Analytical methods : advancing methods and applications
|June 17, 2024
概括
这项研究介绍了一种低成本的计算机视觉系统,使用人工智能来检测酒欺诈. 该方法精确地按品种和品牌分类酒,为酒行业提供快速和环保的解决方案.
科学领域:
- 食品科学 食品科学 食品科学
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 酒是世界上消费量最多的酒精饮料,容易受到欺诈.
- 传统的酒感官分析缺乏精度.
- 工业4.0推动了用于质量控制的AI开发.
研究的目的:
- 开发一种低成本的计算机视觉 (CV) 原型,用于酒分类.
- 利用人工神经网络 (ANN) 进行风格和品牌识别.
- 解决传统酒分析的局限性,并检测欺诈过程.
主要方法:
- 实现了一个CV系统与ANN用于图像采集,处理和分类.
- 分析了111个三倍的酒样本.
- 将数据分离为训练和测试集,用于模型验证.
主要成果:
- 在训练套件上实现了>96%的准确性和精度.
- 在测试组件上获得了78%的准确性和精度.
- 证明CV是酒认证的可行工具.
结论:
- 计算机视觉提供了一种简单,低成本,环保和快速的方法来检测酒欺诈.
- 开发的CV-ANN原型显示了广泛分类能力的潜力.
- 这种技术提高了酒行业的质量控制.
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