ConFruit: Effective Fruit Classification Using CNN Algorithm

Abstract

Fruit is one type of food containing nutrients, vitamins, and minerals that are generally very good for daily consumption. However, various fruit choices make consumers confused about choosing and buying fruit. Many papers have proposed fruit classification to deal with this problem in recent years. Therefore, this study offers a new recommendation model using type to dissect fruit so that buyers can more easily recognize fruit. We collected the primary dataset from Cagle to 3000 fruit images. Based on experiments, our research achieved good accuracy results using the CNN algorithm to classify fruit so that consumers can distinguish between types of fruit. Experimentally demonstrated, we harvested the promised results with better accuracy and small losses than the general fruit classification study.