ArticleFood science and biotechnology2024
Study of active food processing technology using computer vision and AI in coffee roasting.
Article in Food science and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Application of machine learning for quantitative analysis of industrial fermentation using image processing.Food science and biotechnology · 2025Article
- Automation and Optimization of Food Process Using CNN and Six-Axis Robotic Arm.Foods (Basel, Switzerland) · 2024Article
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Authors and funding
3 authors.
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Abstract
In the modern food processing industry, which is more complex than in the past, it is important to utilize real-time computer vision for active food processing technology using artificial intelligence. An integrated solution of computer vision and Deep Learning (DL) technology provides quality control and optimization of food processing in complex environments with obstacles. In this study, Coffee Bean Classification Model (CBCM) made by Machine Learning (ML) showed excellent performance, accurately distinguishing coffee beans through the avoidance of obstacles and empty spaces inside a rotating roasting machine. CBCM achieved a maximum validation accuracy of 98.44% and a minimum validation loss of 5.40% after the fifth epoch. Using a test dataset of 137 samples, CBCM achieved an accuracy of 99.27% and a loss of 2.82%. The developed solution using the CBCM was able to quantify the color change of the coffee beans during roasting.
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