Recognition system for fruit classification based on 8-layer convolutional neural network

Abstract

INTRODUCTION: Automatic fruit classification is a challenging task. The types, shapes, and colors of fruits are all essential factors affecting classification. OBJECTIVES: This paper aimed to use deep learning methods to improve the overall accuracy of fruit classification, thereby improving the sorting efficiency of the fruit factory. METHODS: In this study, our recognition system is based on an 8-layer convolutional neural network (CNN) combined with the RMSProp optimization algorithm to classify fruits. It is verified through 10 times 10-fold crossover validation. CONCLUSION: Our method achieves an accuracy of 91.63%, which is superior to the other four state-of-the-art methods.

Keywords

• fruit classification
• deep learning
• convolutional neural network
• RMSProp