hidden layer信息详情
隐藏层
layer───vt.把…分层堆放;借助压条法;生根繁殖;将(头发)剪成不同层次;n.层,层次;膜;[植]压条;放置者,计划者;vi.形成或分成层次;[植]通过压条法而生根
hidden───n.(Hidden)人名;(英)希登;v.隐藏,躲藏(hide的过去分词);adj.隐藏的
hidden object───隐藏对象
hidden figure───隐藏图形
hidden tag───隐藏标签
outer layer───外层(细胞次生壁外面的一层)
hidden line───[计]隐藏线;隐(藏)线; 隐藏线
hidden figures───隐藏图形
dense layer───[医]致密层
Determining the thickness of "hidden layer" is an important problem in engineering geophysics and engineering geology.───确定“隐蔽层”的厚度,是工程物探、工程地质和工程地震学中的一个重要问题。
Toggling layer visibility no longer makes a hidden layer active.───切换图层可视性不再使一个隐藏层激活。
chosen neural network architecture consisted of one input layer, one hidden layer and the output layer.───我们选择的网络结构包括一个输入层、一个隐含层、一个输出层。
In networks training, connecting weight variables and hidden layer outputs can be optimized alternately.───在网络训练时,可以对连接权值和隐层输出进行交替优化。
This paper proposes a method which can determine the suitable structure in the hidden layer of a neural network.───提出一种确定神经网络隐层中合理结构的方法。
Input layer performs import of samples, hidden layer extracts model characters of samples and output layer presents classification results.───输入层完成分类样本的输入,隐层提取输入样本所隐含的模式特征,将分类结果在输出层表现出来。
model beautiful, hidden layer plate structure synchronization performance is excellent.───机型优美,双层隐藏式平板结构,同步性能优越。
Yet with little damage the result is relatively low. To resolve the problem, augmenting node of hidden layer or number of hidden layer.───只是对于小的损伤识别精度相对差一些,可以通过增大网络隐含层节点数或网络层数来加以解决。
Through the analysis of character features, confirm the input layer, hidden layer and the License of output layer units.───通过对字符特征的分析,确定输入层,隐含层,输出层单元数目。
An improved evolutionary NN of intelligent learning method is proposed. The hidden layer structure and learning parameters (eg. learning rate and momentum) are optimally determined by the method.
It consists of 7 pieces of hidden layer and 5 pieces of data model with membership grade function array.
The equalizer is constructed with decision feedback structure, and an immune algorithm is used to determine the structure and parameters of RBF nonlinear hidden layer.
In this scheme, the inputs of hidden layer neurons are acquired by using the gradient descent method, and the weights and threshold of each neuron are trained using the linear least square method.
For the above reasons, the extended Kalman filter is proposed as RBF learning algorithm, and the biradial function is used in hidden layer.
Before we can compute the remaining eight weights associated with the hidden layer, we must compute the error for each PE.
This paper introduces the methods and techniques of generating multi views based on solid model, and using paper space to print out all graphics by generating hidden layer and layer management.
We have found that a single hidden layer node per about 50 input nodes will satisfy our requirements in imaging applications.
We then select the number of nodes in the first hidden layer.
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