Research Article
Recognition system for fruit classification based on 8-layer convolutional neural network
@ARTICLE{10.4108/eai.17-2-2022.173455, author={Jia-Ji Wang}, title={Recognition system for fruit classification based on 8-layer convolutional neural network}, journal={EAI Endorsed Transactions on e-Learning}, volume={7}, number={23}, publisher={EAI}, journal_a={EL}, year={2022}, month={2}, keywords={fruit classification, deep learning, convolutional neural network, RMSProp}, doi={10.4108/eai.17-2-2022.173455} }- Jia-Ji Wang
Year: 2022
Recognition system for fruit classification based on 8-layer convolutional neural network
EL
EAI
DOI: 10.4108/eai.17-2-2022.173455
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.
Copyright © 2022 Jia-Ji Wang, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
