Companion code for the KST 2025 paper comparing deep learning detectors for cabbage detection and counting in drone imagery. Trains and scores 14 models (Faster R-CNN, SSD, RetinaNet, FCOS, YOLOv8/11/12/26, RT-DETR) on a public UAV dataset, with verified run evidence and released checkpoints.
computer-vision deep-learning uav pytorch remote-sensing yolo faster-rcnn object-detection reproducibility cabbage precision-agriculture retinanet torchvision fcos plant-counting ultralytics yolov8 rt-detr drone-imagery yolo11
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Updated
Sep 25, 2026 - Python