{"id":1735,"date":"2020-12-04T06:55:08","date_gmt":"2020-12-03T23:55:08","guid":{"rendered":"http:\/\/research.binus.ac.id\/airdc\/?p=1735"},"modified":"2021-11-01T10:20:20","modified_gmt":"2021-11-01T03:20:20","slug":"an-implementation-of-convolutional-neural-network-for-coffee-beans-quality-classification-in-a-mobile-information-system","status":"publish","type":"post","link":"https:\/\/research.binus.ac.id\/airdc\/2020\/12\/an-implementation-of-convolutional-neural-network-for-coffee-beans-quality-classification-in-a-mobile-information-system\/","title":{"rendered":"An Implementation of Convolutional Neural Network for Coffee Beans Quality Classification in a Mobile Information System"},"content":{"rendered":"<p style=\"text-align: justify\">Due to its massive trading in world markets, maintaining the quality of coffee is vital for the exporting countries. One approach for quality control is to have a system that can classify coffee beans based on the quality. This system can assist the small-medium coffee enterprises to monitor and secure their procurement. However, the coffee beans quality classification technology is currently unavailable to the small-medium coffee enterprises community. To address this issue, we developed a mobile application powered by a deep-learning-based model to automatically classify coffee beans quality via a mobile phone camera. The deep learning model used is chosen between ResNet-152 and VGG16 based on their performance to classify coffee beans quality. The result shows that ResNet-152 could achieve the highest accuracy of 73.3% and could also be embedded in a functional mobile application.<\/p>\n<p><strong>Robby Janandi and Tjeng Wawan Cenggoro<\/strong><\/p>\n<p><a href=\"https:\/\/www.researchgate.net\/publication\/346563321_An_Implementation_of_Convolutional_Neural_Network_for_Coffee_Beans_Quality_Classification_in_a_Mobile_Information_System\">Read Full Paper<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Due to its massive trading in world markets, maintaining the quality of coffee is vital for the exporting countries. One approach for quality control is to have a system that can classify coffee beans based on the quality. This system can assist the small-medium coffee enterprises to monitor and secure their procurement. However, the coffee [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":2042,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1735","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications"],"_links":{"self":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1735","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/comments?post=1735"}],"version-history":[{"count":1,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1735\/revisions"}],"predecessor-version":[{"id":1737,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/posts\/1735\/revisions\/1737"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/media\/2042"}],"wp:attachment":[{"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/media?parent=1735"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/categories?post=1735"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/research.binus.ac.id\/airdc\/wp-json\/wp\/v2\/tags?post=1735"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}