CBD:咖啡豆数据集 CBD:咖啡豆数据集
Bipin Nair B J1, Abrav Nanda K M1, Shalwin A S1
1Department of Computer Science, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Mysuru, Karnataka, India.
Data in brief
|April 9, 2025
概括
一个新的咖啡豆数据集 (CBD) 包含9个等级的450张图像,有助于咖啡豆的分类. 机器学习模型实现了100%的准确性,增强了自动分级系统.
科学领域:
- 农业科学 农业科学
- 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:
- 咖啡豆质量评估至关重要,但由于主观因素和缺陷而具有挑战性.
- 高质量的数据集对于开发准确的自动咖啡豆分类和分级系统至关重要.
- 当前的方法往往缺乏强大的机器学习模型所需的全面数据.
研究的目的:
- 引入咖啡豆数据集 (CBD),这是一个用于咖啡豆分类的新型高分辨率图像数据集.
- 为培训和评估咖啡分级中的机器学习和深度学习模型提供标准化资源.
- 促进自动咖啡质量评估和分类准确性的进步.
主要方法:
- 收集了450张咖啡豆的高分辨率图像,分为9个不同的等级 (A,AA,AAA,AB,C,PB-I,PB-II,BITS,BULK).
- 确保每班50张图片,来源于喀拉拉邦的Wayanad,以捕捉区域质量变化.
- 使用EfficientNet-B0模型进行初始测试和验证数据集的有效性.
主要成果:
- 咖啡豆数据集 (CBD) 包含9个等级的450张图像,提供多样化的咖啡豆质量表示.
- 在CBD上测试EfficientNet-B0模型的结果是100%的分类准确度.
- 证明了数据集能够支持高性能自动化咖啡豆分类的能力.
结论:
- 在咖啡质量监测方面,CBD是研究人员和行业专业人士的宝贵资源.
- 该数据集有助于开发先进的机器学习算法,用于精确的咖啡豆分类.
- 实现的100%准确性突显了自动咖啡分类系统的重大改进潜力.
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