Image Processing for Classifying the Quality of the Chok-Anan Mango by Simulating the Human Vision using Deep Learning
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Abstract
This paper uses image processing technology with the deep learning methods, which can simulate the human vision to develop a model for examining and classifying the quality of the Chok-Anan mango. The research method, we have collect the image of Chok-Anan mangos and collecting quality classification data, determining quality levels into 4 levels consisting of grade A, B, C and grade D are rotten mangos. The results of the research shown that the use of deep learning by the convolutional neural network (CNN) algorithm for image processing to create a model showing the excellent accuracy at 99.79%. Then, we use the model to develop as a prototype for image classifying of Chok-Anan mangos. The result has found that the success rate of classification at 100%.
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