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ID:37944306
大小:4.19 MB
页数:102页
时间:2019-06-03
《CVPR2012_Deep learning》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、CVPR2012TutorialDeepLearningMethodsforVision(draft)HonglakLeeComputerScienceandEngineeringDivisionUniversityofMichigan,AnnArbor1Featurerepresentationspixel1Learningalgorithmpixel2InputMotorbikesInputspace“Non”-Motorbikespixel2pixel12FeaturerepresentationshandleFeatureLearningrepre
2、sentationalgorithmwheelInputMotorbikesInputspace“Non”-MotorbikesFeaturespacepixel2“handle”pixel1“wheel”3Howiscomputerperceptiondone?State-of-the-art:“hand-crafting”FeatureLearningInputdatarepresentationalgorithmObjectdetectionImageLow-levelObjectdetectionvisionfeatures/classificat
3、ion(SIFT,HOG,etc.)AudioclassificationLow-levelAudioSpeakeraudiofeaturesidentification(spectrogram,MFCC,etc.)4ComputervisionfeaturesSIFTSpinimageHoGRIFTTextonsGLOH5ComputervisionfeaturesSIFTSpinimageHand-craftedfeatures:1.NeedsexpertknowledgeHoGRIFT2.Requirestime-consuminghand-tuni
4、ng3.(Arguably)oneofthelimitingfactorsofcomputervisionsystemsTextonsGLOH6LearningFeatureRepresentations•Keyidea:–Learnstatisticalstructureorcorrelationofthedatafromunlabeleddata–Thelearnedrepresentationscanbeusedasfeaturesinsupervisedandsemi-supervisedsettings–Knownas:unsupervisedf
5、eaturelearning,featurelearning,deeplearning,representationlearning,etc.•Topicscoveredinthistalk:–RestrictedBoltzmannMachines–DeepBeliefNetworks–DenoisingAutoencoders–Applications:Vision,Audio,andMultimodallearning7LearningFeatureHierarchy•DeepLearning3rdlayer–Deeparchitecturescanb
6、e“Objects”representationallyefficient.–Naturalprogressionfrom2ndlayerlowleveltohighlevel“Objectparts”structures.1stlayer–Cansharethelower-level“edges”representationsformultipletasks.Input8Outline•RestrictedBoltzmannmachines•DeepBeliefNetworks•DenoisingAutoencoders•ApplicationstoVi
7、sion•ApplicationstoAudioandMultimodalData9LearningFeatureHierarchy[Relatedwork:Hinton,Bengio,LeCun,Ng,andothers.]Higherlayer:DBNs(Combinationsofedges)Firstlayer:RBMs(edges)Inputimagepatch(pixels)11Note:Noexplicit“pooling.”Describemoreconcretely..RestrictedBoltzmannMachineswithbina
8、ry-valuedinputdata•Representation
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