[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2285":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"view_count":32,"doi":33,"paper":34,"created_at":64},2285,"PetalSpot: an open-source two-stage deep-learning workflow for pixel-level quantification of petal lesions","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112421","PetalSpot: an open-source two-stage deep-learning workflow for pixel-level quantification of petal lesions。Computers and Electronics in Agriculture","PetalSpot：一种用于花瓣病斑像素级量化的开源两阶段深度学习工作流程。",null,"Computers and Electronics in Agriculture","2026-09-11T00:00:00Z","论文",10,false,75,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},16,20,17,14,8,1,"开源两阶段深度学习流程实现花瓣病斑像素级量化，方法新颖且可复用，对花卉病害智能监测有参考价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"智慧农业","农业人工智能","花卉产业","开源工具","植物病害检测",0,"10.1016\u002Fj.compag.2026.112421",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":9,"card":57,"direction":61,"ingested_from":63},"W7212311236",[37,39,41,43,45,47,49,52,54],{"name":38,"orcid":9},"Yao Huang",{"name":40,"orcid":9},"Xiaoqian Cao",{"name":42,"orcid":9},"Fangqi Liu",{"name":44,"orcid":9},"Hong Sha",{"name":46,"orcid":9},"Phurisorn Watcharatpong",{"name":48,"orcid":9},"Ruoheng Jian",{"name":50,"orcid":51},"Wen Chen","https:\u002F\u002Forcid.org\u002F0000-0001-8493-0157",{"name":53,"orcid":9},"Yiqian Fu",{"name":55,"orcid":56},"Zhao Zhang","https:\u002F\u002Forcid.org\u002F0000-0002-7323-5500",{"tldr":58,"method":59,"finding":60,"direction":61,"opportunity":62},"提出开源两阶段深度学习流程PetalSpot，实现花瓣病斑像素级量化。","两阶段深度学习工作流，开源代码，用于花瓣病斑分割与量化。","该流程能对花瓣病斑进行像素级精确量化，且开源可复现。","农业人工智能与决策模型","可迁移至其他作物器官病斑量化，并融合多模态数据提升泛化性。","openalex","2026-09-13T23:30:02.086637Z"]