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标题：cnn 工具箱 matlab 源码程序
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所属分类: 工具箱源码 资源类型：程序源码 文件大小: 109.91 KB 上传时间: 2019-06-18 23:44:00 下载次数: 1 资源积分：1分 提 供 者: admin 20190618234400685
内容：
cnn 工具箱 matlab 源码程序

文件列表（点击上边下载按钮，如果是垃圾文件请在下面评价差评或者投诉）:

cnn/
cnn/+nnet/
cnn/+nnet/+cnn/
cnn/+nnet/+cnn/+layer/
cnn/+nnet/+cnn/+layer/+mixin/
cnn/+nnet/+internal/
cnn/+nnet/+internal/+cnn/
cnn/+nnet/+internal/+cnn/+layer/
cnn/+nnet/+internal/+cnn/+layer/+learnable/
cnn/+nnet/+internal/+cnn/+layer/+util/
cnn/+nnet/+internal/+cnn/+util/
cnn/+nnet/+internal/+cnngpu/
cnn/+nnet/+internal/+cnnhost/
cnn/+nnet/+cnn/+layer/+mixin/ScalarLayerDisplay.m
cnn/+nnet/+cnn/+layer/AveragePooling2DLayer.m
cnn/+nnet/+cnn/+layer/ClassificationOutputLayer.m
cnn/+nnet/+cnn/+layer/Convolution2DLayer.m
cnn/+nnet/+cnn/+layer/CrossChannelNormalizationLayer.m
cnn/+nnet/+cnn/+layer/DropoutLayer.m
cnn/+nnet/+cnn/+layer/FullyConnectedLayer.m
cnn/+nnet/+cnn/+layer/ImageInputLayer.m
cnn/+nnet/+cnn/+layer/Layer.m
cnn/+nnet/+cnn/+layer/MaxPooling2DLayer.m
cnn/+nnet/+cnn/+layer/ReLULayer.m
cnn/+nnet/+cnn/+layer/SoftmaxLayer.m
cnn/+nnet/+cnn/TrainingOptionsSGDM.m
cnn/+nnet/+internal/+cnn/+layer/+learnable/CacheHandle.m
cnn/+nnet/+internal/+cnn/+layer/+learnable/LearnableParameter.m
cnn/+nnet/+internal/+cnn/+layer/+learnable/PredictionLearnableParameter.m
cnn/+nnet/+internal/+cnn/+layer/+learnable/TrainingLearnableParameter.m
cnn/+nnet/+internal/+cnn/+layer/+util/AveragePooling2DGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/AveragePooling2DHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/Convolution2DGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/Convolution2DHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/ExecutionStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/FullyConnectedGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/FullyConnectedHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/LocalMapNorm2DGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/LocalMapNorm2DHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/MaxPooling2DGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/MaxPooling2DHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/ReLUGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/ReLUHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/SoftmaxGPUStrategy.m
cnn/+nnet/+internal/+cnn/+layer/+util/SoftmaxHostStrategy.m
cnn/+nnet/+internal/+cnn/+layer/AveragePooling2D.m
cnn/+nnet/+internal/+cnn/+layer/Convolution2D.m
cnn/+nnet/+internal/+cnn/+layer/CrossEntropy.m
cnn/+nnet/+internal/+cnn/+layer/Dropout.m
cnn/+nnet/+internal/+cnn/+layer/FullyConnected.m
cnn/+nnet/+internal/+cnn/+layer/ImageInput.m
cnn/+nnet/+internal/+cnn/+layer/ImageTransform.m
cnn/+nnet/+internal/+cnn/+layer/ImageTransformFactory.m
cnn/+nnet/+internal/+cnn/+layer/Layer.m
cnn/+nnet/+internal/+cnn/+layer/LocalMapNorm2D.m
cnn/+nnet/+internal/+cnn/+layer/MaxPooling2D.m
cnn/+nnet/+internal/+cnn/+layer/NullLayer.m
cnn/+nnet/+internal/+cnn/+layer/OutputLayer.m
cnn/+nnet/+internal/+cnn/+layer/RandomCropImageTransform.m
cnn/+nnet/+internal/+cnn/+layer/RandomFliplrImageTransform.m
cnn/+nnet/+internal/+cnn/+layer/ReLU.m
cnn/+nnet/+internal/+cnn/+layer/Softmax.m
cnn/+nnet/+internal/+cnn/+layer/ZeroCenterImageTransform.m
cnn/+nnet/+internal/+cnn/+util/CheckpointSaver.m
cnn/+nnet/+internal/+cnn/+util/Precision.m
cnn/+nnet/+internal/+cnn/+util/ProgressDisplayer.m
cnn/+nnet/+internal/+cnn/+util/Reporter.m
cnn/+nnet/+internal/+cnn/+util/TrainingInfoRecorder.m
cnn/+nnet/+internal/+cnn/+util/VectorReporter.m
cnn/+nnet/+internal/+cnn/+util/dummify.m
cnn/+nnet/+internal/+cnn/+util/undummify.m
cnn/+nnet/+internal/+cnn/DataDispatcher.m
cnn/+nnet/+internal/+cnn/DataDispatcherFactory.m
cnn/+nnet/+internal/+cnn/FourDArrayDispatcher.m
cnn/+nnet/+internal/+cnn/ImageDatastoreDispatcher.m
cnn/+nnet/+internal/+cnn/LearnRateSchedule.m
cnn/+nnet/+internal/+cnn/LearnRateScheduleFactory.m
cnn/+nnet/+internal/+cnn/NullSchedule.m
cnn/+nnet/+internal/+cnn/PiecewiseSchedule.m
cnn/+nnet/+internal/+cnn/SeriesNetwork.m
cnn/+nnet/+internal/+cnn/TrainableNetwork.m
cnn/+nnet/+internal/+cnn/Trainer.m
cnn/+nnet/+internal/+cnngpu/isGPUCompatible.m
cnn/+nnet/+internal/+cnngpu/registerGPUDeviceListener.m
cnn/+nnet/+internal/+cnnhost/localMapNormForward2D.m
cnn/+nnet/+internal/+cnnhost/poolingAverageForward2D.m
cnn/+nnet/+internal/+cnnhost/poolingMaxForward2D.m
cnn/+nnet/+internal/+cnnhost/reluForward.m
cnn/+nnet/+internal/+cnnhost/softmaxForward2D.m
cnn/Contents.m
cnn/SeriesNetwork.m
cnn/averagePooling2dLayer.m
cnn/classificationLayer.m
cnn/convolution2dLayer.m
cnn/crossChannelNormalizationLayer.m
cnn/dropoutLayer.m
cnn/fullyConnectedLayer.m
cnn/imageInputLayer.m
cnn/maxPooling2dLayer.m
cnn/reluLayer.m
cnn/softmaxLayer.m
cnn/trainNetwork.m
cnn/trainingOptions.m

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