Nguyen Minh Trieu
ABSTRACT
Mangoes are a common agricultural product in Asia that are sold to other nations. Exported mangoes must meet the standards of different countries, mangoes are classified into different groups for export. A method segmentation for an automatic mango classification system is proposed in this study. The KNN model is applied to segment the mangoes, however, there are many different varieties of mangoes so segmentation is also difficult. Therefore, a self-training model is introduced to increase the accuracy of the KNN model and one can adapt to many mango species. The mangoes are rated by deducting penalty points for failing to meet the requirements that have been established. The system achieved more than 98.7% accuracy for segmentation and 96.67% for the whole classification system.
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Index Terms
- A Study on An Automatic Self-Training Model for Mango Segmentation of Sorting System
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