IV-YOLO:,

Jianxiang Zhang1, Liexiang Huangfu2, Yanling Zhao1

  • 1College of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Jurong, Jiangsu, China.

PubMed
概括

一个新的基于信息旋的渐进融合YOLO (IV-YOLO) 模型增强了在精密农业中的个人大米植物检测. 这种先进的模型有效地分离了附着的植物特征,并减少了背景噪声,以改善监控.

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