An Improved Yolov11n-based Genet for Missing-seed Detection and Counting in an Oblique Hook-shaped Spoon-type Small Precision Seed Metering Device
Year: 2025
Type: article
Abstract: 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.
Source: INMATEH Agricultural Engineering
Authors: Wen SHIWEI, Zhang DEYI, Wei NAISHUO, Ge YAHAO, Chen JUN, Huang TENGLONG, Chen YU, Zhang SHUO, Bo HONGMING, Yuan WEI, Zhang BIN
Institution: Northwest A&F University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4416459952