A Design of Deep Learning Experimentation for Fruit Freshness Detection

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Abstract

Indonesia is a country with a tropical climate so that fruit and vegetable plants can grow easily in Indonesia.Fruits have many good nutrients such as vitamins, proteins and others. But the fruit also has a period where the fruit is said to be fresh fruit.During this time there are still many fruit supplier companies that send fruit unfit for consumption due to lack of accuracy in the process of sorting the fruit when the fruit is taken from the plantation and the entry of other fruit into an improper packaging. Thus, it makes detecting food spoilage from the production stage to consumption is very important. We propose a design of computer vision-based technique usingdeep learning with the Convolutional Neural Network (CNN) model to detect fruit freshness. The specially designed CNN model is then evaluated with public datasets of fruits fresh and rotten for classification derived from Kaggle.

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Valentino, F., Cenggoro, T. W., & Pardamean, B. (2021). A Design of Deep Learning Experimentation for Fruit Freshness Detection. In IOP Conference Series: Earth and Environmental Science (Vol. 794). IOP Publishing Ltd. https://doi.org/10.1088/1755-1315/794/1/012110

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