A 1.4 kg indoor UAV with LiDAR-inertial odometry and 3D multi-object tracking estimated cherry tomato count and weight in a GNSS-denied greenhouse, reaching 94.4% counting and 87.5% weight accuracy on a single 13.2 m lane.
Crop yield prediction using machine learning: A systematic literature review,
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Optimizing Indoor Farm Monitoring Efficiency Using UAV: Yield Estimation in a GNSS-Denied Cherry Tomato Greenhouse
A 1.4 kg indoor UAV with LiDAR-inertial odometry and 3D multi-object tracking estimated cherry tomato count and weight in a GNSS-denied greenhouse, reaching 94.4% counting and 87.5% weight accuracy on a single 13.2 m lane.