4 papers
DINOv3 Meets YOLO26 for Weed Detection in Vegetable Crops
Boyang Deng, Yuzhen Lu
Developing robust models for precision vegetable weeding is currently constrained by the scarcity of large-scale, annotated weed-crop datasets. To address this limitation, this stu…
Detection of On-Ground Chestnuts Using Artificial Intelligence Toward Automated Picking
Kaixuan Fang, Yuzhen Lu, Xinyang Mu
Traditional mechanized chestnut harvesting is too costly for small producers, non-selective, and prone to damaging nuts. Accurate, reliable detection of chestnuts on the orchard fl…
A Comparative Benchmark of Real-time Detectors for Blueberry Detection towards Precision Orchard Management
Xinyang Mu, Yuzhen Lu, Boyang Deng
Blueberry detection in natural environments remains challenging due to variable lighting, occlusions, and motion blur due to environmental factors and imaging devices. Deep learnin…
Semi-Supervised Weed Detection in Vegetable Fields: In-domain and Cross-domain Experiments
Boyang Deng, Yuzhen Lu
Robust weed detection remains a challenging task in precision weeding, requiring not only potent weed detection models but also large-scale, labeled data. However, the labeled data…