Jujube Classification from Images Using Deep Learning Technique - Promboonruang, Suksun; Radasai, Peeraya; Suphaphan, Sirada; Boonrod, Thummarat (Journal of Science Ladkrabang, 2023)
This research presents the extraction of jujubes from photographs using a deep learning technique identify jujubes from photographs using the Inception V3 algorithm. Data sets used in this research are separated into four groups: a,b,c, and d, each group contains 300 images. Test data contains 50 images and data sets used to validate model contains 40 images for training and test models. The experimental results show that Inception V3 has the highest accuracy of 97%, compared to the accuracy of the CNN model of 89% and MobileNet V2 of 86%. It can be used for jujube classification, which is beneficial to farmers. The research findings for the classification data with different quality. The accuracy of the jujube classification model can be further improved.