Oil Palm Condition Monitoring via UAV Imagery Using YOLOv11 Enhanced for Class Imbalance

Abstract

Effective monitoring of oil palm tree conditions is crucial for advancing precision agriculture. Previous studies have primarily focused on detecting and counting oil palm trees, but such approaches are insufficient without the ability to assess tree health. This study proposes a modified YOLOv11 model for oil palm condition detection using the MOPAD dataset, which includes five condition classes. The modification enhances the loss function by introducing class weighting based on data distributi

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