FUNDAMENTALSOFSPEECHRECOGNITION(语音识别基本原理)》(英文)

AReviewofOff-lineHandwrittenChineseCharacterRecognition

经典教材，不用多说：）SpeechandLanguageProcessing:Anintroductiontonaturallanguageprocessing,computationallinguistics,andspeechrecognition.DanielJurafsky&JamesH.Martin.Copyrightc2006,Allrightsreserved.DraftofJune25,2007.Donotcitewithoutpermission.

李子青的人脸识别手册包含人脸检测、人脸跟踪、人脸识别方面的内容。

论文翻译，保留原文排版。
SphereFace:DeepHypersphereEmbeddingforFaceRecognition

Manyresearchgroupsinacademiaandindustryarefocusingontheperformanceimprovementofelectronicnose(E-nose)systemsmainlyinvolvingthree.optimizations,whicharesensitivematerialselectionandsensorarrayoptimization,enhancedfeatureextractionmethodsandpatternrecognitionmethodselection.Foraspecificapplication,thefeatureextractionmethodisabasicpartofthesethreeoptimizationsandakeypointinE-nosesystemperformanceimprovement.Theaimofafeatureextract

生物认证使用BiometricAuthentication在您的应用程序中使用AppleFaceID或TouchID身份验证。
它非常简单易用，可以根据设备处理TouchID和FaceID身份验证。
注意：-面部ID身份验证需要用户的许可才能添加到info.plist中。
NSFaceIDUsageDescriptionThisapprequiresFaceIDpermissiontoauthenticateusingFacerecognition.3.1版中的新功能更新到Swift5.0实现的Result类型作为完成回调版本2.2设置AllowableReuseDuration（以秒为单位）以在用户刚刚使用生物识别技术解锁设备时自动进行身份验证。
当应用

基于深度学习的指静脉识别，python实现

Thistextbookintroducessparseandredundantrepresentationswithafocusonapplicationsinsignalandimageprocessing.Thetheoreticalandnumericalfoundationsaretackledbeforetheapplicationsarediscussed.Mathematicalmodelingforsignalsourcesisdiscussedalongwithhowtousethepropermodelfortaskssuchasdenoising,restoration,separation,interpolationandextrapolation,compression,sampling,analysisandsynthesis,detection,recognition,andmore.Thepresentationiselegantandengaging.SparseandRedundantRepresentationsisintendedforgraduatestudentsinappliedmathematicsandelectricalengineering,aswellasappliedmathematicians,engineers,andresearcherswhoareactiveinthefieldsofsignalandimageprocessing.*Introducestheoreticalandnumericalfoundationsbeforetacklingapplications*Discusseshowtousethepropermodelforvarioussituations*Introducessparseandredundantrepresentations*FocusesonapplicationsinsignalandimageprocessingThefieldofsparseandredundantrepresentationmodelinghasgonethroughamajorrevolutioninthepasttwodecades.Thisstartedwithaseriesofalgorithmsforapproximatingthesparsestsolutionsoflinearsystemsofequations,latertobefollowedbysurprisingtheoreticalresultsthatguaranteethesealgorithms’performance.Withthesecontributionsinplace,majorbarriersinmakingthismodelpracticalandapplicablewereremoved,andsparsityandredundancybecamecentral,leadingtostate-of-the-artresultsinvariousdisciplines.Oneofthemainbeneficiariesofthisprogressisthefieldofimageprocessing,wherethismodelhasbeenshowntoleadtounprecedentedperformanceinvariousapplications.Thisbookprovidesacomprehensiveviewofthetopicofsparseandredundantrepresentationmodeling,anditsuseinsignalandimageprocessing.Itoffersasystematicandorderedexposuretothetheoreticalfoundationsofthisdatamodel,thenumericalaspec

清晰彩色Whenmostpeoplehear“MachineLearning,”theypicturearobot:adependablebutleroradeadlyTerminatordependingonwhoyouask.ButMachineLearningisnotjustafuturisticfantasy,it’salreadyhere.Infact,ithasbeenaroundfordecadesinsomespecializedapplications,suchasOpticalCharacterRecognition(OCR).ButthefirstMLapplicationthatreallybecamemainstream,improvingthelivesofhundredsofmillionsofpeople,tookovertheworldbackinthe1990s:itwasthespamfilter.Notexactlyaself-awareSkynet,butitdoestechnicallyqualifyasMachineLearning(ithasactuallylearnedsowellthatyouseldomneedtoflaganemailasspamanymore).ItwasfollowedbyhundredsofMLapplicationsthatnowquietlypowerhundredsofproductsandfeaturesthatyouuseregularly,frombetterrecommendationstovoicesearch.

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。