Optimizing Annotation Efficiency in Precision Agriculture through Active Learning Strategies
Active learning can reduce annotation effort and improve the efficiency of semantic segmentation models in precision agriculture applications by selectively sampling the most informative images for annotation.
Automated Detection and Sizing of Immature Green Apples in Commercial Orchards using YOLOv8 and 3D Shape Fitting Techniques
Accurate detection and sizing of immature green apples during early growth stages is crucial for yield prediction, pest management, and crop-load management in commercial orchards. This study demonstrates the feasibility of using the state-of-the-art YOLOv8 object detection and instance segmentation algorithm combined with 3D shape fitting techniques to efficiently determine the size of immature green apples in a real-world orchard environment.
Analyzing Neural Networks for Fertilizer Management Zones
Utilizing neural networks to optimize fertilizer management zones based on responsivity to enhance crop yield.
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