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Photoshop移動UI設計從入門到精通
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本書是一本講解如何使用Photoshop軟件進行移動UI設計的實例操作型自學教程,可以幫助UI設計愛好者,特別是手機APP設計人員,提高UI制作能力,拓展移動UI視覺設計的創作思路。本書從兩條線出發,幫助讀者學習Photoshop移動UI設計。一條是橫向案例線,通過對各種類型的素材進行后期制作,如安卓界面、蘋果界面、微軟界面、影音游戲界面等案例,幫助讀者快速精通各類型的移動UI設計方法。另一條是縱向技能線,介紹了Photoshop移動UI設計的核心技法:文字排版+頁面布局+素材處理+色彩校正+界面構成+濾鏡使用等,對移動UI設計的核心技術與精髓內容進行了全面且詳細的講解,幫助讀者快速掌握移動UI設計的精髓。本書共分為15章,內容包括:移動UI的設計常識,移動UI設計的布局原則,移動UI視覺交互設計法則,移動UI的構成元素,Photoshop移動UI快速上手,UI的色彩與風格設計,移動UI文字的編排設計,移動UI圖像的摳取與合成,移動UI圖像特效質感設計,圖標、圖形、按鈕設計,常見蘋果系統UI設計,常見安卓系統UI設計,常見微軟系統UI設計,社交與免費WiFi登錄UI設計,影音與游戲UI設計。全書使用自帶素材,通過對素材的不同處理,制作出精美的界面效果。本書結構清晰,語言簡潔,實例豐富,版式精美,適合Photoshop移動UI設計初、中級讀者閱讀,包括廣大UI設計愛好者、UI設計工作者,同時也可以作為各類計算機培訓中心、技工學校和大中專職業院校的輔導教材。

蔣珍珍 ·專用軟件 ·8.8萬字

Hands/On Simulation Modeling with Python
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EnhanceyoursimulationmodelingskillsbycreatingandanalyzingdigitalprototypesofaphysicalmodelusingPythonprogrammingwiththiscomprehensiveguideKeyFeatures.Learntocreateadigitalprototypeofarealmodelusinghands-onexamples.Evaluatetheperformanceandoutputofyourprototypeusingsimulationmodelingtechniques.UnderstandvariousstatisticalandphysicalsimulationstoimprovesystemsusingPythonBookDescriptionSimulationmodelinghelpsyoutocreatedigitalprototypesofphysicalmodelstoanalyzehowtheyworkandpredicttheirperformanceintherealworld.Withthiscomprehensiveguide,you'llunderstandvariouscomputationalstatisticalsimulationsusingPython.Startingwiththefundamentalsofsimulationmodeling,you'llunderstandconceptssuchasrandomnessandexploredatageneratingprocesses,resamplingmethods,andbootstrappingtechniques.You'llthencoverkeyalgorithmssuchasMonteCarlosimulationsandMarkovdecisionprocesses,whichareusedtodevelopnumericalsimulationmodels,anddiscoverhowtheycanbeusedtosolvereal-worldproblems.Asyouadvance,you'lldevelopsimulationmodelstohelpyougetaccurateresultsandenhancedecision-makingprocesses.Usingoptimizationtechniques,you'lllearntomodifytheperformanceofamodeltoimproveresultsandmakeoptimaluseofresources.Thebookwillguideyouincreatingadigitalprototypeusingpracticalusecasesforfinancialengineering,prototypingprojectmanagementtoimproveplanning,andsimulatingphysicalphenomenausingneuralnetworks.Bytheendofthisbook,you'llhavelearnedhowtoconstructanddeploysimulationmodelsofyourowntoovercomereal-worldchallenges.Whatyouwilllearn.Gainanoverviewofthedifferenttypesofsimulationmodels.Gettogripswiththeconceptsofrandomnessanddatagenerationprocess.Understandhowtoworkwithdiscreteandcontinuousdistributions.WorkwithMonteCarlosimulationstocalculateadefiniteintegral.FindouthowtosimulaterandomwalksusingMarkovchains.Obtainrobustestimatesofconfidenceintervalsandstandarderrorsofpopulationparameters.Discoverhowtouseoptimizationmethodsinreal-lifeapplications.Runefficientsimulationstoanalyzereal-worldsystemsWhothisbookisforHands-OnSimulationModelingwithPythonisforsimulationdevelopersandengineers,modeldesigners,andanyonealreadyfamiliarwiththebasiccomputationalmethodsthatareusedtostudythebehaviorofsystems.ThisbookwillhelpyouexploreadvancedsimulationtechniquessuchasMonteCarlomethods,statisticalsimulations,andmuchmoreusingPython.WorkingknowledgeofPythonprogramminglanguageisrequired.

Giuseppe Ciaburro ·專用軟件 ·8.2萬字

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

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