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Smart agriculture: real-time classification of green coffee beans by using a convolutional neural network
Coffee is an important economic crop and one of the most popular beverages worldwide. The rise of speciality coffees has changed people's standards regarding coffee quality. However, green coffee beans are often mixed with impurities and unpleasant beans. Therefore, this study aimed to solve the problem of time-consuming and labour-intensive manual selection of coffee beans for speciality coffee products. The second objective of the authors’ study was to develop an automatic coffee bean picking system. They first used image processing and data augmentation technologies to deal with the data. They then used deep learning of the convolutional neural network to analyse the image information. Finally, they applied the training model to connect an IP camera for recognition. They successfully divided good and bad beans. The false-positive rate was 0.1007, and the overall coffee bean recognition rate was 93%.
Smart agriculture: real-time classification of green coffee beans by using a convolutional neural network
Coffee is an important economic crop and one of the most popular beverages worldwide. The rise of speciality coffees has changed people's standards regarding coffee quality. However, green coffee beans are often mixed with impurities and unpleasant beans. Therefore, this study aimed to solve the problem of time-consuming and labour-intensive manual selection of coffee beans for speciality coffee products. The second objective of the authors’ study was to develop an automatic coffee bean picking system. They first used image processing and data augmentation technologies to deal with the data. They then used deep learning of the convolutional neural network to analyse the image information. Finally, they applied the training model to connect an IP camera for recognition. They successfully divided good and bad beans. The false-positive rate was 0.1007, and the overall coffee bean recognition rate was 93%.
Smart agriculture: real-time classification of green coffee beans by using a convolutional neural network
Huang, Nen-Fu (author) / Chou, Dong-Lin (author) / Lee, Chia-An (author) / Wu, Feng-Ping (author) / Chuang, An-Chi (author) / Chen, Yi-Hsien (author) / Tsai, Yin-Chun (author)
IET Smart Cities ; 2 ; 167-172
2020-10-13
6 pages
Article (Journal)
Electronic Resource
English
image classification , crops , quality control , convolutional neural nets , speciality coffee products , economic crop , coffee bean recognition rate , learning (artificial intelligence) , coffee quality , real-time classification , automatic coffee bean picking system , convolutional neural network , smart agriculture , beverages , agriculture , unpleasant beans , feature extraction , labour-intensive manual selection , deep learning , green coffee beans , data augmentation technologies , image processing
Metadata by IET is licensed under CC BY 3.0
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