文件名称:python_cnn-master
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CNN的基本结构包括两层，其一为特征提取层，每个神经元的输入与前一层的局部接受域相连，并提取该局部的特征。一旦该局部特征被提取后，它与其它特征间的位置关系也随之确定下来；其二是特征映射层，网络的每个计算层由多个特征映射组成，每个特征映射是一个平面，平面上所有神经元的权值相等。-The basic structure of CNN consists of two layers, one is the feature extraction layer, the input of each neuron is connected with the local acceptance domain of the previous layer, and the local feature is extracted. Once the local feature is extracted, its positional relationship with other features is also determined. The second is the feature mapping layer. Each calculation layer of the network is composed of multiple feature maps. Each feature map is a plane, The weights of all neurons on the plane are equal.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
python_cnn-master/
python_cnn-master/README.md
python_cnn-master/SimpleCNN.ipynb
python_cnn-master/hdf5_generator.py
python_cnn-master/tools/
python_cnn-master/tools/__init__.py
python_cnn-master/tools/__init__.pyc
python_cnn-master/tools/build/
python_cnn-master/tools/build/temp.macosx-10.6-intel-2.7/
python_cnn-master/tools/build/temp.macosx-10.6-intel-2.7/im2col_cython.o
python_cnn-master/tools/classifiers/
python_cnn-master/tools/classifiers/__init__.py
python_cnn-master/tools/classifiers/__init__.pyc
python_cnn-master/tools/classifiers/cnn.py
python_cnn-master/tools/classifiers/cnn.pyc
python_cnn-master/tools/classifiers/convnet.py
python_cnn-master/tools/classifiers/convnet.pyc
python_cnn-master/tools/classifiers/fc_net.py
python_cnn-master/tools/classifiers/fc_net.pyc
python_cnn-master/tools/data_utils.py
python_cnn-master/tools/data_utils.pyc
python_cnn-master/tools/fast_layers.py
python_cnn-master/tools/fast_layers.pyc
python_cnn-master/tools/gradient_check.py
python_cnn-master/tools/gradient_check.pyc
python_cnn-master/tools/im2col.py
python_cnn-master/tools/im2col.pyc
python_cnn-master/tools/im2col_cython.c
python_cnn-master/tools/im2col_cython.pyx
python_cnn-master/tools/im2col_cython.so
python_cnn-master/tools/layer_utils.py
python_cnn-master/tools/layer_utils.pyc
python_cnn-master/tools/layers.py
python_cnn-master/tools/layers.pyc
python_cnn-master/tools/optim.py
python_cnn-master/tools/optim.pyc
python_cnn-master/tools/setup.py
python_cnn-master/tools/solver.py
python_cnn-master/tools/solver.pyc
python_cnn-master/tools/vis_utils.py
python_cnn-master/tools/vis_utils.pyc
python_cnn-master/README.md
python_cnn-master/SimpleCNN.ipynb
python_cnn-master/hdf5_generator.py
python_cnn-master/tools/
python_cnn-master/tools/__init__.py
python_cnn-master/tools/__init__.pyc
python_cnn-master/tools/build/
python_cnn-master/tools/build/temp.macosx-10.6-intel-2.7/
python_cnn-master/tools/build/temp.macosx-10.6-intel-2.7/im2col_cython.o
python_cnn-master/tools/classifiers/
python_cnn-master/tools/classifiers/__init__.py
python_cnn-master/tools/classifiers/__init__.pyc
python_cnn-master/tools/classifiers/cnn.py
python_cnn-master/tools/classifiers/cnn.pyc
python_cnn-master/tools/classifiers/convnet.py
python_cnn-master/tools/classifiers/convnet.pyc
python_cnn-master/tools/classifiers/fc_net.py
python_cnn-master/tools/classifiers/fc_net.pyc
python_cnn-master/tools/data_utils.py
python_cnn-master/tools/data_utils.pyc
python_cnn-master/tools/fast_layers.py
python_cnn-master/tools/fast_layers.pyc
python_cnn-master/tools/gradient_check.py
python_cnn-master/tools/gradient_check.pyc
python_cnn-master/tools/im2col.py
python_cnn-master/tools/im2col.pyc
python_cnn-master/tools/im2col_cython.c
python_cnn-master/tools/im2col_cython.pyx
python_cnn-master/tools/im2col_cython.so
python_cnn-master/tools/layer_utils.py
python_cnn-master/tools/layer_utils.pyc
python_cnn-master/tools/layers.py
python_cnn-master/tools/layers.pyc
python_cnn-master/tools/optim.py
python_cnn-master/tools/optim.pyc
python_cnn-master/tools/setup.py
python_cnn-master/tools/solver.py
python_cnn-master/tools/solver.pyc
python_cnn-master/tools/vis_utils.py
python_cnn-master/tools/vis_utils.pyc
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