JSAI2020

Presentation information

Organized Session

Organized Session » OS-2

[1F3-OS-2a] OS-2 (1)

Tue. Jun 9, 2020 1:20 PM - 3:00 PM Room F (jsai2020online-6)

野中 朋美(立命館大学)、藤井 信忠(神戸大学)

1:20 PM - 1:40 PM

[1F3-OS-2a-01] Proposal of ripeness classification method of avocado using deep learning

〇Hayato Sugimoto1, Ayana Kuno1, Kohei Taniguchi1, Rei Hamakawa1 (1. Chukyo University)

Keywords:Avocado, Ripeness, Non-destructive, Deep learning

Avocados, favorite fruits for many consumers, are to detect if they are ripe or not. There are existing studies on the classification of ripening stages of avocados; however, these studies have not been efficient and convenient for consumers to use. Thus, a different approach that is available to the consumers at large is needed. Here, we propose a method for classifying the ripening stages of avocado using deep learning. This system will help consumers detect a ripe avocado when purchasing or cooking with it. The proposed method uses a new approach to detect avocados and classify them into four ripening stages using two deep learning models from the user's avocado image input.

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