AN IMPROVED YOLOV11N-BASED GENET FOR MISSING-SEED DETECTION AND COUNTING IN AN OBLIQUE HOOK-SHAPED SPOON-TYPE SMALL PRECISION SEED METERING DEVICE

A lightweight vision-based model, GENet, is proposed to overcome the limitations of conventional missing-seed detection systems, which are highly sensitive to seed characteristics and constrained by slow response and complex configuration. Deployed on a small precision seeder featuring an oblique hook-shaped spoon-type metering device, GENet integrates Ghost Modules, C3Ghost structures, and an ECA attention mechanism. Experiments demonstrate an mAP50–95 of 85.2%, accuracy of 99.9%, and 185 FPS inference speed on the Jetson AGX Xavier platform, while reducing model parameters by over 40%. Validation on the JPS-12 test bench confirms its robustness, providing an efficient solution for intelligent precision seeding.