文件名称:Dropout1
- 所属分类：
- 2D图形编程
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2016-02-27
- 文件大小：
- 18.28mb
- 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
Code for Deep Learning for Detecting Robotic Grasps.Intended to be a simple codebase which will allow you to load the grasping
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code.-Code for Deep Learning for Detecting Robotic Grasps.Intended to be a simple codebase which will allow you to load the grasping
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code.
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code.-Code for Deep Learning for Detecting Robotic Grasps.Intended to be a simple codebase which will allow you to load the grasping
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
Dropout1
........\backpropData
........\............\backprogation.mat
........\............\classify_error.mat
........\............\classify_weights.mat
........\data
........\....\graspModes24.mat
........\....\graspTestData.mat
........\....\graspTrainData.mat
........\minFunc
........\.......\ArmijoBacktrack.m
........\.......\autoGrad.m
........\.......\autoHess.m
........\.......\autoHv.m
........\.......\autoTensor.m
........\.......\callOutput.m
........\.......\conjGrad.m
........\.......\dampedUpdate.m
........\.......\example_minFunc.m
........\.......\example_minFunc_LR.m
........\.......\isLegal.m
........\.......\lbfgs.m
........\.......\lbfgsC.c
........\.......\lbfgsC.mexa64
........\.......\lbfgsC.mexglx
........\.......\lbfgsC.mexmac
........\.......\lbfgsC.mexmaci
........\.......\lbfgsC.mexmaci64
........\.......\lbfgsC.mexw32
........\.......\lbfgsC.mexw64
........\.......\lbfgsUpdate.m
........\.......\logistic
........\.......\........\LogisticDiagPrecond.m
........\.......\........\LogisticHv.m
........\.......\........\LogisticLoss.m
........\.......\........\mexutil.c
........\.......\........\mexutil.h
........\.......\........\mylogsumexp.m
........\.......\mchol.m
........\.......\mcholC.c
........\.......\mcholC.mexmaci64
........\.......\mcholC.mexw32
........\.......\mcholC.mexw64
........\.......\mcholinc.m
........\.......\minFunc.m
........\.......\minFunc_processInputOptions.m
........\.......\polyinterp.m
........\.......\precondDiag.m
........\.......\precondTriu.m
........\.......\precondTriuDiag.m
........\.......\rosenbrock.m
........\.......\taylorModel.m
........\.......\WolfeLineSearch.m
........\recTraining
........\...........\auroc.m
........\...........\bsxfunwrap.m
........\...........\dirtyRegCostL0.m
........\...........\histtest.m
........\...........\inverseSigmoid.m
........\...........\l2rowscaled.m
........\...........\logSumExpL0Cost.m
........\...........\multimodalRegL0.m
........\...........\nogpu
........\...........\.....\.svn
........\...........\.....\....\all-wcprops
........\...........\.....\....\entries
........\...........\.....\....\prop-base
........\...........\.....\....\props
........\...........\.....\....\text-base
........\...........\.....\....\.........\gather.m.svn-base
........\...........\.....\....\.........\gpuArray.m.svn-base
........\...........\.....\....\tmp
........\...........\.....\....\...\prop-base
........\...........\.....\....\...\props
........\...........\.....\....\...\text-base
........\...........\.....\gather.m
........\...........\.....\gpuArray.m
........\...........\pNormGrad.m
........\...........\README.txt
........\...........\roc1.m
........\...........\rocdemo.m
........\...........\runBackpropMultiReg1.m
........\...........\runSAEMultiSparse.m
........\...........\scaleAndBiasWeights.m
........\...........\scaleMaskByModes2.m
........\...........\smoothedAbs.m
........\...........\smoothedL1Cost.m
........\...........\softmaxBackpropCostMultiReg.m
........\...........\softmaxInitCost.m
........\...........\sparseAECostBinaryGenBias.m
........\...........\sparseAECostMultiRegWeighted.m
........\...........\trainGraspRecMultiSparse.m
........\...........\W.jpg
........\...........\Whist.m
........\util
........\....\caseWiseWhiten.m
........\....\getSurfNorm.m
........\....\graspPCDToRGBDImage.m
........\....\interpMaskedData.m
........\....\orientedRGBDRectangle.m