Development of fig fruit ripeness classification using convolutional neural network / Siti Juliana Abu Bakar ... [et al.]

• 主要な著者: Abu Bakar, Siti Juliana, Musa, Hanis Raihana, Osman, Mohamed Syazwan, M Abdul Kader, Mohamed Mydin, Eka Cahyani, Denis, Setumin, Samsul
• フォーマット: 論文
• 言語: English
• 出版事項: Universiti Teknologi MARA Cawangan Pulau Pinang 2024
• 主題: Pulau Pinang; Universiti Teknologi MARA
• オンライン･アクセス: https://ir.uitm.edu.my/id/eprint/104957/1/104957.pdf; https://ir.uitm.edu.my/id/eprint/104957/; https://uppp.uitm.edu.my/

This study presents the design and evaluation of a deep convolutional neural network (CNN) model for accurately classifying fig ripeness stages. Traditionally, fruit ripeness classification has been conducted manually, which presents several drawbacks, including heavy reliance on human labor and inc...