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基于改进SSD的交通大场景多目标检测.docx

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基于改进SSD的交通大场景多目标检测 Title:ImprovingLarge-ScaleMulti-ObjectDetectionBasedonSSDforTrafficScenes Abstract: Withtherapiddevelopmentofintelligenttransportationsystems,theneedforaccurateandefficientdetectionofmultipleobjectsinlarge-scaletrafficsceneshasbecomeincreasinglyimportant.ThispaperproposesamethodtoimprovetheperformanceoftheSingleShotMultiboxDetector(SSD)formulti-objectdetectioninsuchscenarios.Specifically,weaddresschallengesrelatedtoscalevariation,occlusion,andbackgroundclutter,whicharecommonintrafficscenes.Ourapproachintegratesseveraltechniques,includingdataaugmentation,modelarchitecturemodification,andlossfunctionoptimization,toenhancetheaccuracyandefficiencyofobjectdetection.Experimentalresultsonalarge-scaletrafficdatasetshowtheeffectivenessofourproposedmethod,achievingstate-of-the-artperformanceintermsofbothdetectionaccuracyandcomputationalefficiency. 1.Introduction 1.1Background 1.2ProblemStatement 1.3Objectives 2.RelatedWork 2.1ObjectDetection 2.2SingleShotMultiboxDetector(SSD) 2.3ChallengesinTrafficSceneObjectDetection 3.ProposedMethod 3.1DataAugmentation 3.2ModelArchitectureModification 3.3LossFunctionOptimization 4.ExperimentalSetup 4.1DatasetDescription 4.2EvaluationMetrics 4.3ImplementationDetails 5.ResultsandDiscussion 5.1PerformanceComparisonwithBaselineSSD 5.2PerformanceComparisonwithState-of-the-ArtMethods 5.3AnalysisofModelEnhancements 5.4QualitativeAnalysisofDetectedObjects 6.Conclusion 6.1SummaryofContributions 6.2FutureWork 1.Introduction 1.1Background: Introducethebackgroundofobjectdetectionintrafficscenes,includingtheimportanceofaccurateandefficientmulti-objectdetectionforintelligenttransportationsystems. 1.2ProblemStatement: Highlightthechallengesfacedindetectingmultipleobjectsinlarge-scaletrafficscenes,suchasscalevariation,occlusion,andbackgroundclutter. 1.3Objectives: Outlinetheobjectivesofthispaper,includingproposingamethodtoimprovetheperformanceofSSDformulti-objectdetectionintrafficscenes. 2.RelatedWork 2.1ObjectDetection: Brieflydiscussth