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Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t...
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Peiyu Wang, Huting Wang, Ruoyu Zhang, Rong Hu, Beibei Hao and Jie Huang
Cotton processing is the process of converting harvested seed cotton into lint by cleaning, ginning, and cleaning the lint. The real-time acquisition of lint parameters during processing is critical in improving cotton processing quality and efficiency. ...
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Xingdong Sun, Yukai Zheng, Delin Wu and Yuhang Sui
The key technology of automated apple harvesting is detecting apples quickly and accurately. The traditional detection methods of apple detection are often slow and inaccurate in unstructured orchards. Therefore, this article proposes an improved YOLOv5s...
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Hui Liu, Kun Li, Luyao Ma and Zhijun Meng
Headland boundary identification and ranging are the key supporting technologies for the automatic driving of intelligent agricultural machinery, and they are also the basis for controlling operational behaviors such as autonomous turning and machine lif...
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Wolfgang Jarausch, Miriam Runne, Nora Schwind, Barbara Jarausch and Uwe Knauer
Apple proliferation (AP) is an economically important disease in many apple-growing regions caused by ?Candidatus Phytoplasma mali? which is spread by migrating psyllid vectors on a regional scale. As infected trees in orchards are the only inoculum sour...
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