Fruits and Vegetables Recognition System in Dzongkha Using Visual Geometry Group Network

Abstract

English speaking among the youth is gaining popularity in Bhutan. The Ministry of Education and Dzongkha Development Commission have been trying to promote the national language through different strategies. Furthermore, developed interesting learning materials in Dzongkha. However, youth find it difficult even to name common fruits and vegetables in Dzongkha, and this is an increasing concern. The purpose of this study was to develop an automatic fruit recognition system in Dzongkha using machine learning techniques. Ten classes of fruits and 17 classes of veg- etables that are found in Bhutan are considered for the study. The fruits and vegetable datasets were downloaded from Kaggle and Websites. Furthermore, images were augmented and rotated every 15 degrees. The dataset comprised 405000 images. The model was trained and deployed using customized VGGNet and Gradio. The training and vali- dation accuracy of the proposed model was 97.76% and 97.80% respectively.