文件名称:deepGraspingCode
- 所属分类：
- matlab例程
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2014-04-18
- 文件大小：
- 150kb
- 下载次数：
- 0次
- 提 供 者：
- Youmei******
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
用深度学习做的机械抓取的目标识别，对桌面上的问题进行检测并识别出抓取的区域以及抓取方式-Learning to do with the depth of the object recognition mechanical crawl on the issues on the desktop to detect and identify the areas and crawl crawl way
(系统自动生成,下载前可以参看下载内容)
下载文件列表
deepGraspingCode
................\minFunc
................\data
................\recTraining
................\processData
................\loadData
................\util
................\detection
................\weights
................\minFunc\logistic
................\recTraining\nogpu
................\detection\detectionFromKinect
................\.........\detectionUtils
................\.........\detectionFromData
................\recTraining\nogpu\.svn
................\...........\.....\....\tmp
................\...........\.....\....\props
................\...........\.....\....\text-base
................\...........\.....\....\prop-base
................\...........\.....\....\tmp\props
................\...........\.....\....\...\text-base
................\...........\.....\....\...\prop-base
................\README.txt
................\loadProcessAndTrain.m
................\minFunc\lbfgsUpdate.m
................\.......\mcholC.mexmaci64
................\.......\lbfgsC.mexw32
................\.......\rosenbrock.m
................\.......\lbfgsC.mexmaci
................\.......\lbfgs.m
................\.......\lbfgsC.mexw64
................\.......\autoHv.m
................\.......\lbfgsC.mexmac
................\.......\mcholC.c
................\.......\lbfgsC.mexglx
................\.......\lbfgsC.mexa64
................\.......\conjGrad.m
................\.......\autoHess.m
................\.......\example_minFunc.m
................\.......\taylorModel.m
................\.......\polyinterp.m
................\.......\callOutput.m
................\.......\precondDiag.m
................\.......\lbfgsC.mexmaci64
................\.......\WolfeLineSearch.m
................\.......\minFunc_processInputOptions.m
................\.......\precondTriuDiag.m
................\.......\precondTriu.m
................\.......\autoTensor.m
................\.......\minFunc.m
................\.......\mcholC.mexw64
................\.......\dampedUpdate.m
................\.......\lbfgsC.c
................\.......\mchol.m
................\.......\mcholC.mexw32
................\.......\example_minFunc_LR.m
................\.......\isLegal.m
................\.......\ArmijoBacktrack.m
................\.......\mcholinc.m
................\.......\autoGrad.m
................\data\graspModes24.mat
................\....\bgNums.mat
................\recTraining\multimodalRegL0.m
................\...........\sparseAECostBinaryGenBias.m
................\...........\logSumExpL0Cost.m
................\...........\sparseAECostMultiRegWeighted.m
................\...........\softmaxBackpropCostMultiReg.m
................\...........\smoothedL1Cost.m
................\...........\softmaxInitCost.m
................\...........\runBackpropMultiReg.m
................\...........\runSAEBinary.m
................\...........\pNormGrad.m
................\...........\inverseSigmoid.m
................\...........\scaleAndBiasWeights.m
................\...........\smoothedAbs.m
................\...........\dirtyRegCostL0.m
................\...........\bsxfunwrap.m
................\...........\l2rowscaled.m
................\...........\scaleMaskByModes2.m
................\...........\runSAEMultiSparse.m
................\...........\trainGraspRecMultiSparse.m
................\...........\README.txt
................\processData\scaleDataByChannel.m
................\...........\scaleChannels.m
................\...........\getChanStds.m
................\...........\scaleDataByChannelStds.m
................\...........\dropMeanByFeat.m
................\...........\combineAllFeat.m
................\...........\whitenDataCaseWiseDepth.m
................\...........\splitGraspData.m
................\...........\getGraspingSplit.m
................\...........\chanStdsToFeat.m
................\...........\processGraspData.m
................\loadData\getNewFeatFromRGBD.m
................\........\loadGraspingInstanceImYUVNorm.m
................\........\loadAllGraspingDataImYUVNormals.m
................\util\resizeMaskedImage2.m
................\....\interpMaskedData.m