RTMDet-AS: an improved real-time instance segmentation model for tomato harvesting based on attention mechanism and SIoU loss
RTMDet-AS is presented, a robust instance segmentation network tailored to address the challenges of cluttered backgrounds, dense fruit clusters, and the strict efficiencyaccuracy trade-off required for edge computing in unstructured greenhouses with a 96.7 FPS inference rate and fewer computational efforts.