一个深度神经网络 in English translation

• a deep neural network

Examples of using 一个深度神经网络 in Chinese and their translations into English

一个深度神经网络具有两个以上的隐藏层。
A deep neural network has more than two hidden layers.

所以她把这项工作交给一个深度神经网络来处理。
So she's giving the job to a deep neural network.

研究员接下来使用一个深度神经网络（VGG-Face）创建特征。
The researchers then used a deep neural network(VGG-Face) to create features.

多伦多大学的AlexKrizhevsky创建了一个深度神经网络，能够从一百万个样本中自动学习识别图像。
Alex Krizhevsky of the University of Toronto created a deep neural network that automatically learned to recognize images from 1 million examples.

研究人员利用37236个头部CT图像，来训练一个深度神经网络，让其识别图像中是否包含关键或非关键的发现。
Researchers used 37,236 head CT scans to train a deep neural network to identify whether an image contained critical or non-critical findings.

一个深度神经网络可能有10到20个隐含层，而一个典型的神经网络可能只有几层。
A deep neural network might have 10 to 20 hidden layers, whereas a typical neural network may have only a few.

一家无人机公司最近也描述了一个深度神经网络，可以在复杂的真实环境中自动操作无人机。
A drone company recently described a deep neural network that autonomously flies drones in complex real-world environments.

研究人员利用37236个头部CT图像，来训练一个深度神经网络，让其识别图像中是否包含关键或非关键的发现。
Oermann and colleagues used 37,236 head CT scans to train a deep neural network to identify if an image contained critical findings.

AlphaGo通过训练一个深度神经网络来预测棋局位置的值，利用数百万场过去的比赛作为训练数据。
AlphaGo worked by training a deep neural network to predict the value of board positions, using millions of past games as training data.

研究人员利用37236个头部CT图像，来训练一个深度神经网络，让其识别图像中是否包含关键或非关键的发现。
Utilizing 37,236 head CT scans, researchers trained a deep neural network to identify if an image consisted of critical or non-critical findings.

本周，你将建立一个深度神经网络，你想要多少层就有多少层！!
This week, you will build a deep neural network, with as many layers as you want!

图2：给定位置周围的区域会被栅格化（rasterized），然后被传递给一个深度神经网络。
Figure 2: The area surrounding a given location is rasterized and passed to a deep neural network.

最后，但不是不重要，硬件需求对于运行一个深度神经网络模型是至关重要的。
Last but not the least, hardware requirements are essential for running a deep neural network model.

正如可以从论文的题目中推测出来的那样，涉及的回归模型是一个深度神经网络）。
(As you can probably infer from the title of the paper, the regression model in question was a deep neural network.).

正如你可能从本文的标题推断的，解决这个问题的回归模型是一个深度神经网络）.
(As you can probably infer from the title of the paper, the regression model in question was a deep neural network.).

但是，要进行学习，一个深度神经网络需要做的不仅仅是在各层神经网络中传递信息。
To learn, however, a deep neural net needed to do more than just send messages up through the layers in this fashion.

当然，在数学的角度上，你可以找出来哪一个深度神经网络节点被激活了。
Indeed, mathematically, you can find out which nodes of a deep neural network were activated.

一个深度神经网络在“学习”过数以千计的狗的照片后，能像人一样准确地识别出从未见过的照片中的狗。
After a deep neural network has“learned” from thousands of sample dog photos, it can identify dogs in new photos as accurately as people can.

不同的一点是，今年我们使用Deepnet，这是一个深度神经网络，而不是去年使用的集成模型（ensembles）。
For a change, this year we will use deepnets, BigML deep neural networks, instead of the ensembles that we used last year.

例如，一个「深度」神经网络GoogLeNet使用22个图层和数百万个参数将图像分类为1000个不同的类别。
For example GoogLeNet, a“deep” neural network, uses 22 layers with millions of parameters to classify images into 1000 distinct categories.'.