The Evolution of Precision Agriculture
The Evolution of Precision Agriculture。Smart Agricultural Technology
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Modeling the global potential of smart farming innovations
全球5公里尺度评估五类智慧农业创新在农田的盈利性与扩散潜力。
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Multi-Source Remote Sensing Fusion and Deep Learning for Intelligent Precision Agriculture
综述多源遥感融合与深度学习在精准农业感知-决策-执行框架中的应用与趋势。
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Ensemble Machine Learning for Farm-Level Rainfall Forecasting Based on Satellite Observations
基于卫星观测，用集成机器学习为农场尺度做降雨预报。
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UAV-based RGB imagery and supervised–unsupervised machine learning for estimating sorghum biomass and grain yield under water and nitrogen stress
用无人机RGB影像与机器学习估算水分氮胁迫下高粱生物量和产量。
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AI-enabled UAV-based Soil Organic Carbon Mapping in Arid Environments: A Pilot Study Protocol
提出一套无人机高光谱结合AI的干旱区土壤有机碳制图标准化试点方案。
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An information-driven air–ground collaborative framework for UAV-based tillage defect identification and re-tillage path optimization
提出空地协同框架，用无人机识别耕整缺陷并优化补耕路径。
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Deep learning-based classification of wet direct seeded rice, broadcasted direct seeded rice and transplanted rice using drone imagery for precision agriculture
用无人机可见光影像和深度学习模型区分直播稻、湿直播稻与移栽稻三种水稻种植方式。
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Multi-grained image-text retrieval in farmland remote sensing via multimodal large language models
提出农田遥感图文跨模态检索任务，构建数据集并提出FarmMGR框架实现语言驱动检索。
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