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

[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.