Identify the Color and Shape of Eggplant Using Back Propagation Method

Abstract

Currently, artificial neural networks are being developed as a tool that can help human tasks. The main purpose of this study is to identify the structure of an eggplant, in order to distinguish the type of eggplant. This study empirically tested the shape and color of several eggplants using the back propagation neural network learning method. The data is obtained from an image that will be entered into the program. The data used in the identification process are two photos containing two types of eggplant, the first eggplant is green and round and the next eggplant is purple and oval. The results of the identification process using this back propagation from the tests that have been carried out previously, the highest calculation results obtained with the best results using a learning rate of 0.7 and epoch iterations of 500 and producing an accuracy of 73.33%.

Keywords

• neural networks, back propagation, accuracy, eggplants