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convolution layer
Traducere "convolution layer" în chineză
卷积层
In a fully convolutional network, we initialize the transposed convolution layer for upsampled bilinear interpolation.
在全卷积网络中，可以将转置卷积层初始化为双线性插值的上采样。
The convolution layer, as the name suggests, convolves the input with a set of learned weights or filters, each producing one feature map in the output image.
卷积层，顾名思义，将包含一套权值或过滤器的输入进行卷积，在输出图中生成一张特征图。
The shape of some layers can change. The convolution layer, for example, adds a dimension and changes the value of length and width according to the characteristics of the convolution kernel (filter).
某些层的形状是会发生变化的。例如卷积层，会增加一个维度，并且根据卷积核（过滤器）的特征改变长宽的值。
It is divided into input, convolution layer, pooling layer (sampling layer), full connection and output. Each layer compresses the most important identifying information and transmits it to the next layer.
分为输入、卷积层、池化层（采样层）、全连接和输出。每一层都将最重要的识别信息进行压缩，并传导至下一层。
Figure 2. Structure of group-cross convolution layer
图 2 编组-交叉卷积层结构示意图
If we use Xavier to randomly initialize the transposed convolution layer, what will happen to the result?
如果将转置卷积层改用Xavier随机初始化，结果有什么变化？
For the DeepBench convolution kernel (Fig. 2) we also include results for the open-source Intel optimized convolution layer implementation using libxsmm.
针对 DeepBench 的卷积内核（图 2 ） ， 我们利用 libxsmm ［3 ］ ， 进行开源英特尔优化的卷积层实施，并记录实施结果。
Convolution layer: to help extract features, the deeper (multi-layer) convolutional neural network will extract more specific features, and the more shallow network extraction will be more obvious.
卷积层：帮助提取特征，越深（层数多）的卷积神经网络会提取越具体的特征，越浅的网络提取越浅显的特征。
In a fully convolutional network, we initialize the transposed convolution layer for upsampled bilinear a \(1\times 1\) convolution layer, we use Xavier for randomly initialization.
在全卷积网络中，我们将转置卷积层初始化为双线性插值的上采样。对于 \（1\times 1\） 卷积层，我们采用 Xavier 随机初始化。
Flatten layer is used to make the multidimensional input one-dimensional, commonly used in the transition from the convolution layer to the full connected layer.
Flatten层将输入"压平"，即把多维的输入一维化，常用在从卷积层到全连接层的过渡。
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