gtm218IntroductiontoSmoothManifoldsbyjohnlee

C++实现的香港中文大学徐立等人的《ImageSmoothingviaL0GradientMinimization》一文。

WorkswithUnityCloudBuildiOS&AndroidsupportWindows10UWPsupportWebGLsupportWin&Mac&LinuxStandalonesupportPreviewsupportintheEditorOpenCVforUnityisanAssetsPluginforusingOpenCV3.4.2fromwithinUnity.OfficialSite|ExampleCode|AndroidDemoWebGLDemo|Tutorial&DemoVideo|Forum|APIReference|SupportModulesFeatures:-SincethispackageisacloneofOpenCVJava,youareabletousethesameAPIasOpenCVJava3.4.2(link).-Youcanimageprocessinginreal-timebyusingtheWebCamTexturecapabilitiesofUnity.(real-timefacedetectionworkssmoothlyoniPhone5)-ProvidesamethodtointerconversionofUnity'sTexture2DandOpenCV'sMat.-IDisposableisimplementedinmanyclasses.Youcanmanagetheresourceswiththe“using”statement.-Examplesofintegrationwithotherpublisherassetsareavailable.（e.g.PlayMaker,NatCam,NatCorder）ExampleCodeusingOpenCVforUnityisavailable.MarkerBasedARExampleMarkerLessARExampleFaceTrackerExampleFaceSwapperExampleFaceMaskExampleRealTimeFaceRecognitionExampleGoogleVRwithOpenCVforUnityExampleKinectwithOpenCVforUnityExampleAVProwithOpenCVforUnityExampleHoloLenswithOpenCVforUnityExamplePlayMakerActionsforOpenCVforUnityNatCamwithOpenCVForUnityExampleNatCorderwithOpenCVForUnityExampleOpenCVforUnityusesOpenCVunder3-clauseBSDLicense;seeThird-PartyNotices.txtfileinpackagefordetails.SystemRequirementsBuildWinStandalone&PreviewEditor:Windows7orlaterBuildMacStandalone&PreviewEditor:OSX10.9orlater

Thedatasignalobtainedbyusingthenear-infraredspectroscopydetectorincludestheinformationofthecomponenttobetested,includingthenoiseofvariousinstruments,suchashigh-frequencyrandomnoise,baselinedrift,spuriousinformation,backgroundofthesample.Therefore,beforedataanalysis,thespecificsignalmeasurementandsamplesystemshouldbeprocessedreasonably,andtheinfluenceofvariousnon-targetfactorsonthedetectionsignalinformationshouldbeweakenedoreveneliminated,whichlaysafoundationforestablishingastableandreliablemathematicalmodel.Co妹妹onlyuseddatapreprocessingmethodsincludedatanormalizationprocessing(meancentering,normalization,standardnormaltransformation,etc.),highfrequencynoisefiltering(convolutionsmoothing,Fouriertransform,wavelettransform,etc.),differentialderivationofsignals,andBaselinecorrection,etc.

unity图像人脸画面视觉识别零碎插件OpenCVforUnity2.3.4所支持的Unity版本：5.6.6及以上版本WorkswithUnityCloudBuildiOS&AndroidsupportWindows10UWPsupportWebGLsupportWin&Mac&LinuxStandalonesupportPreviewsupportintheEditorOpenCVforUnityisanAssetsPluginforusingOpenCV4.0.0fromwithinUnity.Features:-SincethispackageisacloneofOpenCVJava,youareabletousethesameAPIasOpenCVJava4.0.0(link).-Youcanimageprocessinginreal-timebyusingtheWebCamTexturecapabilitiesofUnity.(real-timefacedetectionworkssmoothlyoniPhone5)-ProvidesamethodtointerconversionofUnity'sTexture2DandOpenCV'sMat.-IDisposableisimplementedinmanyclasses.Youcanmanagetheresourceswiththe“using”statement.-Examplesofintegrationwithotherpublisherassetsareavailable.（e.g.PlayMaker,NatCam,NatCorder）ExampleCodeusingOpenCVforUnityisavailable.MarkerBasedARExampleMarkerLessARExampleFaceTrackerExampleFaceSwapperExampleFaceMaskExampleRealTimeFaceRecognitionExampleGoogleVRwithOpenCVforUnityExampleKinectwithOpenCVforUnityExampleAVProwithOpenCVforUnityExampleHoloLenswithOpenCVforUnityExamplePlayMakerActionsforOpenCVforUnityNatCamwithOpenCVForUnityExampleNatCorderwithOpenCVForUnityExampleMagicLeapwithOpenCVForUnityExample

本书讲述了SPH无网格方法的基本思想，操作引见以及优势

IonicStudioisapowerfulappbuilderthatdeliversasmoothdeveloperexperienceforteamsbuildingwithIonic.Getstartedwiththefastestandeasiestwaytocreateaward-winningcross-platformapps,fromasingletool.

(1)数学(2)高级微积分(3)数学分析(4)右不连续方程(5)控制系统(6)非光滑函数(7)国外研讨生经典教材

该代码用IDL8.5编写，利用Savitzky-GolaySmoothingFilter对图像进行SG滤波处理，输入平滑图像文件

ObiRopeWithObiRopeyoucancreateropesinamatterofseconds,withcompletecontrolovertheirshapeandbehavior.Theropescancollidewiththeenvironmentandwitheachother,andcanbeattachedtorigidbodies.AvailableforWindows,Mac,iOSandAndroid.LinksObiWebsiteCo妹妹unityandSupportForumFeatures:-Proceduralsmoothmeshgenerationusingsplines,completewithtangentspaceupdatingandnormalmapsupport.Noneedtomanuallygenerategeometryforyourropes.-Changeropelengthatruntime.-Tearable/cuttablerope.-Closedloops.-Two-wayrigidbodyinteraction.-Modularsolver:don'twasteperformance,onlyusetheconstraintsyourropeneeds.-Permoduleadjustablesolveriterationcount.-Bendingconstraints.-Perparticlepinconstraints.

在日常工作中，钉钉打卡成了我生活中不可或缺的一部分。然而，有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚，我总是得牢记打开钉钉应用，点击"工作台"，再找到"考勤打卡"进行签到。有时候因为工作忙碌，会忘记打卡，导致考勤异常，影响当月的工作评价。而且，由于我使用的是苹果手机，有时候系统更新后，钉钉的某些功能会出现异常，使得打卡变得更加麻烦。 另外，我的家人使用的是安卓手机，他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说，每次打卡都是一次挑战。他们总是担心自己会操作失误，导致打卡失败。 为了解决这些烦恼，我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习，我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。