Information fusion in smart agriculture: machine learning applications and future research directions
核心期刊综述,主题高度相关,但正文被反爬拦截,无法获取实质内容,时效性差。
综述系统分析 ML 在农业中的应用,强调多源数据融合(遥感、IoT、生物数据)对精准农业的关键作用。围绕四个研究目标展开:(1)探索 ML 在收获前、收获中、收获后阶段的整合;(2)展示多源数据融合的益处;(3)研究当前研究趋势;(4)汇编关键公共数据集。重点提及 Transformer、GAN、联邦学习、持续学习和可解释 AI 等新兴方法在应对现代农业挑战中的作用。
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