CONVOLUTIONAL - 翻译成中文

• 卷积
• 神经

在 英语 中使用 Convolutional 的示例及其翻译为 中文

In 2012, a version of the Deep Neural Network(DNN), called the Convolutional Neural Network(CNN), demonstrated a huge leap in accuracy.
在2012年，称为卷积神经网络(CNN)的深层神经网络(DNN)的版本显示了精确度的巨大飞跃。

It works on convolutional neural networks and/or recurrent neural networks, and can also run on both CPU and GPU.
它作用于卷积神经网络和/或复发性神经网络，也可以运行在两个CPU和GPU。

We will show you how to train and optimize basic neural networks, convolutional neural networks, and long short-term memory networks.
我们将为你展示如何训练和优化基础神经网络、卷积神经网络和长短期记忆神经网络。

Vision tasks using line art, medical imaging, or other domains very different to standard photos are likely to require retraining convolutional layers, however.
然而，使用线条艺术，医学成像或与标准照片非常不同的其他领域的视觉任务可能需要再训练卷积层。

Then, using NVIDIA GPUs with the cuDNN-accelerated TensorFlow deep learning framework, they trained a convolutional neural network to predict cancer diagnoses based on breast imaging.
然后，他们使用NVIDIAGPU和cuDNN加速的TensorFlow深度学习框架，训练卷积神经网络根据乳腺影像预测癌症诊断。

The Reed- Solomon code, like the convolutional code, is a transparent code.
里德-所罗门码，如同卷积码一样，是一种透明码。

We trained a convolutional neural network(CNN) to predict the probability that a given Kepler signal is caused by a planet.
我们训练了一个卷积神经网络(CNN)来预测给定开普勒信号由行星引起的可能性。

Batch normalization usually happens after the convolutional layer but before the activation function gets applied(a so-called“leaky” ReLU in the case of YOLO).
批标准化通常发生在卷积层之后，激活函数（YOLO中的ReLU函数）之前。

A convolutional network is composed of one or more convolutional layers(filtering layers), followed by a fully connected multilayer neural network.
一个卷积网络由一个或多个卷积层（过滤层）组成，然后是一个完全连接的多层神经网络。

Entitled"ImageNet Classification with Deep Convolutional Neural Networks," it is available here.
我们来看看《ImageNetClassificationwithDeepConvolutionalNeuralNetworks》这篇文章在讲什么。

Figure 12: The encoder comprises of a convolutional neural network, followed by a fully connected layer.
图12：这个编码器包含一个卷积神经网络，后面跟着一个全连接层。

The first successful applications of Convolutional Networks were developed by Yann LeCun in 1990s.
LeNet：第一个成功的卷积神经网络应用，是YannLeCun在上世纪90年代实现的。

Linear regression, classification, and even image classification with convolutional network fall into this category.
线性回归、分类，甚至是卷积网络的图像分类都属于这一类。

But if you have a convolutional neural network and you're doing a 17 x 17 multiplier, that may be overkill.
但如果你有一个卷积神经网络并且要做一个17×17的乘法器，那可能就有点过头了。

Their first Convolutional Neural Network was called LeNet-5 and was able to classify digits from hand-written numbers.
他们的第一个卷积神经网络称为lenet-5，能够对手写数字中的数字进行分类。

When we hear about Convolutional Neural Network(CNNs), we typically think of Computer Vision.
当我们听到卷积神经网络（ConvolutionalNeuralNetwork,CNNs）时，往往会联想到计算机视觉。

Convolutional neural networks(CNN or deep convolutional neural networks, DCNN) are quite different from most other networks.
卷积神经网络(Convolutionalneuralnetworks,CNN,orDeepconvolutionalneuralnetworks,DCNN)和大多数其他网络完全不同。

Convolutional neural network(CNN): A type of neural networks that identifies and makes sense of images.
Convolutionalneuralnetwork(CNN)(卷积神经网络):一种识别和理解图像的神经网络。

They used an ensemble of only 5 convolutional neural networks and got the error rate of 0.21 percent.
他们只使用了由5个卷积神经网络组成的集合，并将错误率控制在0.21%。

That's followed by a convolutional layer with multiple filters, then a max-pooling layer, and finally a softmax classifier.
在卷积层的后面跟着多个过滤器，然后是一个max-poolinglayer，最后是一个softmax分类器。