Transformer模型在智慧农业中的应用现状与展望OA

Smart agriculture is regarded as a core direction of modern agriculture.Significant advantages are demonstrated by the Transformer model,through its self-attention mechanism,in capturing long-sequence dependencies and integrating multi-source data,offering a new pathway for the intelligent upgrading of agriculture.An analysis was presented of the model's application in scenarios such as crop growth monitoring,disaster early warning,and production management.Challenges including high model complexity,insufficient data adaptability,and weak interpretability were highlighted.Future development trends such as lightweight design,few-shot learning,and multi-technology collaboration were also outlined,with the aim of providing references for the large-scale application of the technology.