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Applied Deep Learning and Computer Vision for Self/Driving Cars
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Exploreself-drivingcartechnologyusingdeeplearningandartificialintelligencetechniquesandlibrariessuchasTensorFlow,Keras,andOpenCVKeyFeatures*Buildandtrainpowerfulneuralnetworkmodelstobuildanautonomouscar*Implementcomputervision,deeplearning,andAItechniquestocreateautomotivealgorithms*OvercomethechallengesfacedwhileautomatingdifferentaspectsofdrivingusingmodernPythonlibrariesandarchitecturesBookDescriptionThankstoanumberofrecentbreakthroughs,self-drivingcartechnologyisnowanemergingsubjectinthefieldofartificialintelligenceandhasshifteddatascientists'focustobuildingautonomouscarsthatwilltransformtheautomotiveindustry.Thisbookisacomprehensiveguidetousedeeplearningandcomputervisiontechniquestodevelopautonomouscars.Startingwiththebasicsofself-drivingcars(SDCs),thisbookwilltakeyouthroughthedeepneuralnetworktechniquesrequiredtogetupandrunningwithbuildingyourautonomousvehicle.Onceyouarecomfortablewiththebasics,you'lldelveintoadvancedcomputervisiontechniquesandlearnhowtousedeeplearningmethodstoperformavarietyofcomputervisiontaskssuchasfindinglanelines,improvingimageclassification,andsoon.Youwillexplorethebasicstructureandworkingofasemanticsegmentationmodelandgettogripswithdetectingcarsusingsemanticsegmentation.Thebookalsocoversadvancedapplicationssuchasbehavior-cloningandvehicledetectionusingOpenCV,transferlearning,anddeeplearningmethodologiestotrainSDCstomimichumandriving.Bytheendofthisbook,you'llhavelearnedhowtoimplementavarietyofneuralnetworkstodevelopyourownautonomousvehicleusingmodernPythonlibraries.Whatyouwilllearn*ImplementdeepneuralnetworkfromscratchusingtheKeraslibrary*Understandtheimportanceofdeeplearninginself-drivingcars*GettogripswithfeatureextractiontechniquesinimageprocessingusingtheOpenCVlibrary*Designasoftwarepipelinethatdetectslanelinesinvideos*Implementaconvolutionalneuralnetwork(CNN)imageclassifierfortrafficsignalsigns*Trainandtestneuralnetworksforbehavioral-cloningbydrivingacarinavirtualsimulator*Discovervariousstate-of-the-artsemanticsegmentationandobjectdetectionarchitecturesWhothisbookisforIfyouareadeeplearningengineer,AIresearcher,oranyonelookingtoimplementdeeplearningandcomputervisiontechniquestobuildself-drivingblueprintsolutions,thisbookisforyou.Anyonewhowantstolearnhowvariousautomotive-relatedalgorithmsarebuilt,willalsofindthisbookuseful.Pythonprogrammingexperience,alongwithabasicunderstandingofdeeplearning,isnecessarytogetthemostofthisbook.

Sumit Ranjan;Dr. S. Senthamilarasu ·專用軟件 ·5.4萬字

PPT云課堂教學法
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當前,教師要想使教學能吸引“網絡一代”學生,借助互聯網技術來進一步完善和升級PPT教學法,乃是大勢所趨。《PPT云課堂教學法》創造性地將幻燈片設計與“云課堂”在線教學相互結合,是國內第一本明確提出“PPT云課堂教學法”的教學技術專著。以提升教師PPT設計能力為基礎,本書推薦一種國際流行的“快課”技術。與傳統電教不同,快課技術是一種專供教師自己動手設計各種電子課件的快捷實用性技能,能使教師快速生成各種形式的微課、慕課等網絡課件。本書將快課技術與教學PPT幻燈片設計、微課、慕課制作創造性地結合為一體,以筆記本電腦為基本工具,輔之以易學易用的快課軟件,使每一名有志于教學改革的教師都能輕松地自主實現備課電子化和教學信息化。整體而言,本書為廣大教師提供一整套簡單易用的教學PPT幻燈片和微課、翻轉課堂、慕課和私播課的技術解決方案,內容新穎而具獨創性,既有扎實的理論基礎,又包括眾多具有操作性的設計方法,簡單實用且富有藝術設計色彩,將教學PPT的設計提升到一個新層次,有助于實現教師職業發展空間的最大化延伸。本書適用于各學科教師的教學技能培訓,也可用作師范院校的教材和參考書。

趙國棟 趙興祥主編 ·專用軟件 ·15.5萬字

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