基于深度学习的车载垃圾图像分类与识别系统设计与实现
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中图分类号：U463.6 文献标识码：A 文章编号：1003-8639（2025）08-0086-03
【Abstract】 Urban domestic waste management is the main link that affcts the efciency of environment and resourceutilization，andthecurrent garbagecollctionvehicle mainlyreliesontheworkers toclasifythegarbage，which isineficient，theclassificationispronetoerrors，and therearerisksinthe working environmentoftheworkers.Theuse of imagerecognitiontechnologytoautomaticallyidentifythecategoryofgarbageisakeydirectiontoimprovethelevelof garbagedisposal intelligence，deeplearning technologycaneffectivelyidentifythecharacteristicsofobjectsinthepicture， andshow goodresultsinthe garbage imageclasification task.Therefore，thispaper discusses how todesignadep learning-basedautomaticgarbageimage clasificationandrecognitionsystem，inthe hopeof improvingtheeficiencyand accuracyof on-board garbageclassification.
【Key words】 deep learning； on-board garbage； image classificatior
0 引言
1车载垃圾图像分类与识别系统的设计背景
城市每天产生大量生活垃圾，高效的分类处理对环境保护和资源回收至关重要。（剩余4143字）
