A CONVOLUTIONAL NEURAL NETWORK - 翻译成中文

• 卷积神经网络

在 英语 中使用 A convolutional neural network 的示例及其翻译为 中文

In this step-by-step Keras tutorial, you will learn how to build a convolutional neural network in Python!
在这个循序渐进的Keras教程中，你将学习如何在Python中构建卷积神经网络！!

The architecture of YOLO is simple, it's just a convolutional neural network.
YOLO的架构是很简单的，它就是一个卷积神经网络：.

Seeing AI started with a February 2014 effort to create a convolutional neural network that could help find and identify surrounding objects.
SeeingAI的开发始于2014年2月，开发人员曾试图创建一个能发现并识别周围物体的卷积神经网络。

With Caffe, you can very easily build a convolutional neural network(CNN) for image classification.
借助Caffe，你可以非常轻松地构建用于图像分类的卷积神经网络（CNN）。

Stemming from BVLC's work in vision and image recognition, Caffe's core strength is its ability to model a Convolutional Neural Network(CNN).
以BVLC在视觉和图像识别领域的成果为基础，Caffe的核心优势在于能够对卷积神经网络（CNN）建模。

Unlike in C++, Python users can write a convolutional neural network from scratch under 50 lines.
与C++不同，Python用户可以从零开始编写一个卷积神经网络，用不了50行代码。

Watson soaked up all that information into a convolutional neural network with tens of thousands of tags in its vocabulary.
Watson将所有这些信息都融合到具有数万标签的卷积神经网络。

Here we propose an approach based on a convolutional neural network pre-trained on a large-scale image classification task.
在这里，我们提出了一种基于在大规模图像分类任务上预训练的卷积神经网络的方法。

In this part, you will create a Convolutional Neural Network that is able to detect various objects in images.
在这部分中，你将创建一个能够检测影像中各种对象的卷积神经网络。

The most successful deep learning network is a convolutional neural network(CNN) developed by Yann LeCun.
最成功的深度学习网络是由YannLeCun开发的卷积神经网络（CNN）。

I used a convolutional Neural Network as a predictor on our dataset.
我使用卷积神经网络（ConvolutionalNeuralNetwork）作为我们的数据集的预测器。

Attention can also be used on the interface between a convolutional neural network and an RNN.
注意力还能用于卷积神经网络和RNN之间的界面。

Understand how to build a convolutional neural network, including recent variations such as residual networks..
理解如何搭建一个神经网络，包括最新的变体，例如残余网络.

In this part of the series we learned how to build a convolutional neural network.
本篇教程中，我们学习了如何构建一个神经网络。

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。

For a convolutional neural network, each filter is automatically adjusted to help with the intended outcome.
卷积神经网络的每个滤波器都自动调整，以帮助预期的结果。

Xiang Zhang, et al. use a character-based representation of text as input for a convolutional neural network.
XiangZhang等人使用一个基于字符的文本表示作为卷积神经网络的输入。

Every layer within a convolutional neural network applies a filter across the image to pick up specific patterns or features.
卷积神经网络中的每个层都在图像上应用过滤器来拾取特定的图案或特征。

Adam Harley created amazing visualizations of a Convolutional Neural Network trained on the MNIST Database of handwritten digits[13].
AdamHarley创建了一个卷积神经网络的可视化结果，使用的是MNIST手写数字的训练集13。

A Deep Learning model(such as a Convolutional Neural Network) does not try to understand the entire problem at once.
一个深度学习模型（如卷积神经网络）并不会试图即刻理解整个问题所在。