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中文说明：
用于检测机器人抓取的深度学习代码。旨在成为一个简单的代码库，允许您加载抓取数据集、处理和增白它、训练网络和执行抓取检测。目前不包含更先进的评估代码（交叉验证，评分等），或代码的两个通过系统我添加辍学到这个代码。
English Description：
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.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
........\...........\.....\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
........\...........\Whist.m
........\util
........\....\caseWiseWhiten.m
........\....\getSurfNorm.m
........\....\graspPCDToRGBDImage.m
........\....\interpMaskedData.m
........\....\orientedRGBDRectangle.m
........\....\padImage.m
........\....\padMaskedImage2.m
........\....\pointsInAARect.m
........\....\readGraspingPcd.m
........\....\removeOutliers.m
........\....\resizeMaskedImage2.m
........\....\rgb2yuv.m
........\....\rotMat2D.m
........\....\smartInterpMaskedData.m
........\....\unpackRGBFloat.m
........\weights
........\.......\graspWFinal.mat