Fig. 5
From: PFLO: a high-throughput pose estimation model for field maize based on YOLO architecture
The pipeline and network architecture of PFLO. Upper panel: field images undergo data preprocessing (standardizing keypoints and generating bounding boxes) before entering the PFLO model. Lower panel: the architectural design featuring RepNCSPELAN4_SE blocks (yellow), dynamic upsampling modules (Dy_Sample, light blue), Multi-SEAM modules (orange) for occlusion handling, and RepConv-based detection heads (teal) that predict both bounding boxes and keypoints simultaneously