/ 北大去雨算法python版
北大去雨算法python版
北大去雨算法python版
去雨算法的PYTHON完成，Rainstreakscanseverelydegradethevisibility,whichcausesmanycurrentcomputervisionalgorithmsfailtowork.Soitisnecessarytoremovetherainfromimages.Weproposeanoveldeepnetworkarchitecturebasedondeepconvolutionalandrecurrentneuralnetworksforsingleimagederaining.Ascontextualinformationisveryimportantforrainremoval,wefirstadoptthedilatedconvolutionalneuralnetworktoacquirelargereceptivefield.Tobetterfittherainremovaltask,wealsomodifythenetwork.Inheavyrain,rainstreakshavevariousdirectionsandshapes,whichcanberegardedastheaccumulationofmultiplerainstreaklayers.Weassigndifferentalpha-valuestovariousrainstreaklayersaccordingtotheintensityandtransparencybyincorporatingthesqueeze-and-excitationblock.Sincerainstreaklayersoverlapwitheachother,itisnoteasytoremovetheraininonestage.Sowefurtherdecomposetherainremovalintomultiplestages.Recurrentneuralnetworkisincorporatedtopreservetheusefulinformationinpreviousstagesandbenefittherainremovalinlaterstages.Weconductextensiveexperimentsonbothsyntheticandreal-worlddatasets.Ourproposedmethodoutperformsthestate-of-the-artapproachesunderallevaluationmetrics. 本软件ID:10731006
去雨算法的PYTHON完成，Rainstreakscanseverelydegradethevisibility,whichcausesmanycurrentcomputervisionalgorithmsfailtowork.Soitisnecessarytoremovetherainfromimages.Weproposeanoveldeepnetworkarchitecturebasedondeepconvolutionalandrecurrentneuralnetworksforsingleimagederaining.Ascontextualinformationisveryimportantforrainremoval,wefirstadoptthedilatedconvolutionalneuralnetworktoacquirelargereceptivefield.Tobetterfittherainremovaltask,wealsomodifythenetwork.Inheavyrain,rainstreakshavevariousdirectionsandshapes,whichcanberegardedastheaccumulationofmultiplerainstreaklayers.Weassigndifferentalpha-valuestovariousrainstreaklayersaccordingtotheintensityandtransparencybyincorporatingthesqueeze-and-excitationblock.Sincerainstreaklayersoverlapwitheachother,itisnoteasytoremovetheraininonestage.Sowefurtherdecomposetherainremovalintomultiplestages.Recurrentneuralnetworkisincorporatedtopreservetheusefulinformationinpreviousstagesandbenefittherainremovalinlaterstages.Weconductextensiveexperimentsonbothsyntheticandreal-worlddatasets.Ourproposedmethodoutperformsthestate-of-the-artapproachesunderallevaluationmetrics. 本软件ID:10731006
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