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English(EN) DefoliationCAM: An Edge-AI System for Real-Time Insect Defoliation Severity Assessment in Grapevines

边缘AI系统DefoliationCAM实时评估葡萄藤虫害损失

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了DefoliationCAM (D-CAM)，一个用于实时评估葡萄藤虫害落叶严重程度的边缘AI系统。该系统利用YOLOX-Nano模型进行枝条定位，并使用轻量级的MobileNet分类器对田间收集的图像进行损害等级分类。D-CAM将斑块预测汇总为非线性全局落叶严重程度 (NGDS) 分数，该分数已通过专家评分进行了验证，并与既定的害虫管理阈值一致。该系统采用自主部署和太阳能供电，证明了其在远程监测和及时害虫管理决策方面的可行性。 AI

影响 通过自动视觉检查，实现农业中更精确、更及时的害虫管理。

排序理由 该条目描述了一个在arXiv预印本上发布的新系统和方法论。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

边缘AI系统DefoliationCAM实时评估葡萄藤虫害损失

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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Fuchen Li, Wei-Zhen Liang, Pin-Chu Lai, Xin Qiao, Jingqiu Chen, Haw Yen, Zonglin Yanga, Chi-En Chiang, Rudolph Avalos, Abbigail L. Rath ·

    DefoliationCAM：一种用于葡萄藤实时虫害落叶严重程度评估的边缘AI系统

    arXiv:2610.20879v1 Announce Type: new Abstract: Insect-induced defoliation threatens grapevine health and yield, yet severity assessment relies on subjective manual scouting. We developed DefoliationCAM (D-CAM), a solar-powered edge AI system that estimates canopy defoliation and…

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