Real-Time Detection of Ripe Oil Palm Fresh Fruit Bunch based on YOLOv4

• Published in: IEEE access Vol. 10; p. 1
• Main Authors: Lai, Jin Wern, Ramli, Hafiz Rashidi, Ismail, Luthffi Idzhar, Hasan, Wan Zuha Wan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Cameras; Data acquisition; Data models; Deep learning; Detection; Fresh Fruit Bunch; Fruit Maturity; Human error; Object detection; oil palm; Oil palm trees; Oils; Palm oil; Real time; Real-time systems; Training; Vegetation; YOLO; YOLOv4

Fresh Fruit Bunch (FFB) is the main ingredient in palm oil production. Harvesting FFB from oil palm trees at its peak ripeness stage is crucial to maximise the oil extraction rate (OER) and quality. In current harvesting practices, misclassification of FFB ripeness can occur due to human error, resu...