Deep Learning based Coffee Beans Quality ScreeningShow others and affiliations
2022 (English)In: Proceedings 2022 IEEE International Conference on e-Business Engineering ICEBE 2022: 14–16 October 2022 Bournemouth, United Kingdom, IEEE, 2022, p. 271-275Conference paper, Published paper (Refereed)
Abstract [en]
Coffee bean quality screening is a time-consuming work, and its workload increases abruptly with the rapid development of coffee beverage consumer market. In this work, a CNN-based classifier is developed to categorizing the coffee beans into sour, black, broken, moldy, shell, insect damage and good beans. The screening test results show that the screening accuracy could reach more than 90% for all other beans except for shell beans (88%). Therefore, the proposed method is feasible and promising. Moreover, a cost-effective automatic coffee bean screening system using the developed classifier is manufactured and implemented for a local company.
Place, publisher, year, edition, pages
IEEE, 2022. p. 271-275
Keywords [en]
Cost effectiveness, Deep learning, Coffee bean screening, Coffee beans, Coffee beverages, Consumer market, Convolutional neural network, Cost effective, Insect damage, Screening system, Screening tests, Convolutional neural networks, coffee beans screening
National Category
Computer graphics and computer vision
Research subject
Virtual Production Development (VPD); Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-22314DOI: 10.1109/ICEBE55470.2022.00054Scopus ID: 2-s2.0-85148621439ISBN: 978-1-6654-9244-7 (electronic)ISBN: 978-1-6654-9245-4 (print)OAI: oai:DiVA.org:his-22314DiVA, id: diva2:1740758
Conference
2022 IEEE International Conference on e-Business Engineering, ICEBE 2022, 14-16 October 2022 Bournemouth, United Kingdom
Note
© 2022 IEEE
2023-03-022023-03-022025-09-29Bibliographically approved