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Real-Time Detection of Coffee Cherry Ripeness Using YOLOv11

This study aims to develop a real-time coffee fruit ripeness detection system using the YOLOv11 algorithm to assist farmers in determining the optimal harvest time. The dataset comprises 302 images categorized into three ripeness levels: ripe, semi-ripe, and unripe. Model training was conducted on G...

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Uloženo v:
Hlavní autoři: Anis Ilyana, Nurdin Nurdin, Maryana Maryana
Médium: Artigo
Jazyk:Inglês
Vydáno: Politeknik Negeri Batam 2025-08-01
Edice:Journal of Applied Informatics and Computing
Témata:
python
automated detection system
coffee fruit
yolov11
machine learning
On-line přístup:https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/9735
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