Wan Hyun Cho1, Sang Kyoon Kim2, Myung Hwan Na1, In Seop Na3,*
CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4003-4024, 2021, DOI:10.32604/cmc.2021.018758
Abstract Fruit processing devices, that automatically detect the freshness and ripening stages of fruits are very important in precision agriculture. Recently, based on deep learning, many attempts have been made in computer image processing, to monitor the ripening stage of fruits. However, it is time-consuming to acquire images of the various ripening stages to be used for training, and it is difficult to measure the ripening stages of fruits accurately with a small number of images. In this paper, we propose a prediction system that can automatically determine the ripening stage of fruit by a combination of deep neural networks (DNNs)… More >
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