This is an outdated version published on 2023-06-19. Read the most recent version.

Fruits and Vegetables Recognition System in Dzongkha

Authors

  • Karma Wangchuk
  • Tsheten Dorji
  • Parshu Ram Dhungyel
  • Pema Galey
  • Manoj Chhetri

DOI:

https://doi.org/10.17102/v8004

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.

Published

2023-06-19 — Updated on 2023-06-19

Versions

How to Cite

Wangchuk, K., Dorji, T., Ram Dhungyel, P., Galey, P., & Chhetri, M. (2023). Fruits and Vegetables Recognition System in Dzongkha. Zorig Melong- A Technical Journal of Science, Engineering and Technology, 8(1). https://doi.org/10.17102/v8004