Deep learning-based fruit quality classification for customer service

Nguyen Vu Minh Nguyen 1, Thao T.P Nguyen 2, Phuong T.K Pham 3 and Giao N. Pham 4, *

1 Funix Program, Dept. of Software Engineering, FPT University, Vietnam.
2 Faculty. of Computer Science and Engineering, Thuy-Loi University, Hanoi, Vietnam.
3 Information Technology Faculty, Hanoi University of Industry, Hanoi, Vietnam.
4 Department of Computing Fundamentals, FPT University, Hanoi, Vietnam.
 
Research Article
International Journal of Science and Research Archive, 2024, 11(01), 1064–1068.
Article DOI: 10.30574/ijsra.2024.11.1.0159
Publication history: 
Received on 21 December 2023; revised on 27 January 2024; accepted on 30 January 2024
 
Abstract: 
Consumers always select and buy good quality fruits and vegetable. Selection criteria depend upon the freshness, shape, appearance, color, aroma and sturdiness at the first go. The taste and the shelf life come after that. As fruits play main role in day to day life, the grading of fruits is necessary in evaluating agricultural produce. The present existing technology are also used for fruit quality managing purpose but they are not more effective. There are some disadvantages like less reliability, less efficiency and less accuracy. In this paper, we would like to present a design and integration fruit quality classification solution for customer service. The purpose of this integration is to develop a service to classify the quality of fruits for customer in applications in agriculture, market or logistic.
 
Keywords: 
Deep Learning; Computer Vision; Image Processing; Fruit disease Detection; Fruit Quality Classification; and Fruit Quality Criteria
 
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