Precision Diagnosis of Apple Leaf Diseases Across Infection Stages via Web-Based Analysis
提出基于YOLOv8-MHSA与SAM的网页系统，实现苹果叶片病害多感染阶段实时检测与分级。
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#作物叶片病害识别
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没有这个标签，内容接近An Intelligent IoT-Based Framework for Plant Disease Detection and Crop Advisory Using CNN and ESP32
构建ESP32物联网与CNN结合的植物病害检测及作物咨询系统。
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基于QYmax叶绿素荧光成像和改进LCRNet模型的小麦白粉病智能识别与诊断,登Frontiers in Plant Science
用QYmax叶绿素荧光成像与改进LCRNet实现小麦白粉病高精度识别。
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From Laboratory to Field: Frozen Foundation-Model Features Toward Robust Plant Disease Recognition
From Laboratory to Field: Frozen Foundation-Model Features Toward Robust Plant Disease Recognition。Smart Agricultural Technology
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Smart Agriculture Using ESP32
提出基于ESP32与CNN的智能农业系统，实现环境监测与叶片病害实时检测。
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A study on the identification of wheat powdery mildew using chlorophyll fluorescence imaging
该研究利用叶绿素荧光成像与深度学习识别小麦白粉病并分级。
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Lightweight Hybrid CNN-Transformer Network for Robust Maize Leaf Disease Detection and Edge Deployment
构建轻量MobileNetV3-Small框架实现玉米叶片病害分类并评估边缘部署。
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A Nightshade-SWIN Transformer-Based Framework for Enhanced Multi-Crop Plant Disease Classification
提出Nightshade-SWIN框架，用Swin Transformer提升茄科多作物叶片病害分类
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