卷积层和下采样层一般会取若干个,采用卷积层和下采样层交替设置,即一个卷积层连接一个下采样层,下采样层后再连接一个卷积层,依此类推。由于卷积层的英语翻译

卷积层和下采样层一般会取若干个,采用卷积层和下采样层交替设置,即一个卷

卷积层和下采样层一般会取若干个,采用卷积层和下采样层交替设置,即一个卷积层连接一个下采样层,下采样层后再连接一个卷积层,依此类推。由于卷积层中输出特征面的每个神经元与其输入进行局部连接,并通过对应的连接权值与局部输入进行加权求和再加上偏置值,得到该神经元输入值
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结果 (英语) 1: [复制]
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Convolution layer and the lower layer will generally take the sample number, and the lower layer was sampled convolution layers are alternately arranged, i.e. a connection layer of a convolution downsampling layer, a connecting layer after downsampling convolution layer, and so on. Due to the convolution output of each neuron layer as its input connected to local surface characteristics, and by summing the weighted corresponding value of the local input connection weights plus a bias value, obtained input value of the neural element
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结果 (英语) 2:[复制]
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Convolution layer and subsampling layer will generally take several, using the convolution layer and the subsampling layer alternate setting, that is, a convolution layer is connected to a subsampling layer, the subsampling layer is then connected to a convolution layer, and so on. The input value of the neuron is obtained because each neuron in the convolution layer has a local connection to its input and is weighted sum and bias edifyby by the corresponding connection weight and local input.
正在翻译中..
结果 (英语) 3:[复制]
复制成功!
The convolution layer and the lower sampling layer are generally selected, and the convolution layer and the lower sampling layer are alternately set, that is, a convolution layer is connected with a lower sampling layer, and then the lower sampling layer is connected with a convolution layer, and so on. Each neuron in the output feature plane of convolution layer is locally connected with its input, and the input value of the neuron is obtained by the weighted sum of the corresponding connection weight and the local input plus the bias value<br>
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