What is the translation of " GOOGLENET " in English?

• googlenet

Examples of using Googlenet in Chinese and their translations into English

GoogleNet的优势有：.
The advantages of GoogleNet are:.

分类网络已经从AlexNet发展到GoogLeNet，再到ResNet，等等。
Classification networks have evolved from AlexNet to GoogLeNet to ResNet and beyond.

GoogleNet的优势在于：.
The advantages of GoogleNet are:.

而Keras可以让我们很轻易地下载像VGG16、GoogleNet、ResNet这样的预训练网络。
Keras allows you easliy to download pretrained networks like VGG16, GoogleNet and ResNet.

GoogLeNet有数个后续版本。
There are several follow-up versions to the GoogLeNet.

视频展示了GoogLeNet和AlexNet模型处理相同图像的情况。
The above video is showing the GoogLeNet and AlexNet models processing the same set of images.

GoogLeNet还有几个后续版本，最近的是Inception-v4。
There are also several followup versions to the GoogLeNet, most recently Inception-v4.

从现有网络（如AlexNet或GoogLeNet）起步，并输入包含以往未知类的新数据。
You start with an existing network, such as AlexNet or GoogLeNet, and feed in new data containing previously unknown classes.

GoogLeNet将多个设计精细的Inception块和其他层串联起来。
GoogLeNet connects multiple well-designed Inception blocks with other layers in series.

许多标准的深度学习模型，如LSTM、AlexNet和GoogLeNet，都可以作为Neon的预训练模型。
Many standard deep learning models such as LSTM, AlexNet, and GoogLeNet, are available as pre-trained models for Neon.

GoogLeNet将多个精细设计的Inception块和其他层串联起来。
GoogLeNet connects multiple well-designed Inception blocks with other layers in series.

虽然ResNet的主体架构跟GoogLeNet的类似，但ResNet结构更简单，修改也更方便。
Although the main architecture of ResNet is similar to that of GoogLeNet, ResNet's structure is simpler and easier to modify.

此外，和GoogLeNet类似，它也在分类层之后连接了一个全局平均池化层。
Also, similar to GoogLeNet, it uses a global average pooling followed by the classification layer.

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.'.

GoogLeNet是一个22层的CNN，是2014年ILSVRC的赢家，top5的错误率为6.7％。
GoogLeNet is a 22 layer CNN and was the winner of ILSVRC 2014 with a top 5 error rate of 6.7%.

例如，著名的22层的Googlenet模型可以从不同的库里下载，例如GoogLeNetinKeras。
For example, the famous 22-layer Googlenet model is available for download in different models(e.g. Keras model).

GoogLeNet模型的计算复杂，而且不如VGG那样便于修改通道数。
The GoogLeNet model is computationally complex, so it is not as easy to modify the number of channels as in VGG.

这样的层级结构使理解概念以及从视觉角度呈现它们变得更加简单（除非我们只想创建GoogLeNet的数据艺术图）。
Such hierarchy makes it simpler both to understand concepts and present them visually(unless we just want to create data-artsy diagrams of GoogLeNet).

与GoogleNet类似，这些“残差模块”相互叠加，从而形成一个完整的网络的。
Now similar to GoogleNet, these residual modules are stacked one over the other to form a complete end-to-end network.

随后，深度神经网络日益流行，并出现了多种优秀变体，比如AlexNet、GoogLeNet、VGGNet、ResNet。
Subsequently, deep neural networks became increasingly popular, and many excellent variants emerged, such as AlexNet, GoogLeNet, VGG Net, and ResNet.

GoogLeNet是第一个引入了“CNN层次并不总是必须依次叠加”概念的模型之一。
GoogLeNet was one of the first models that introduced the idea that CNN layers didn't always have to be stacked up sequentially.

本文由GoogleAI研究人员描述了他们的新物体检测系统GoogLeNet，它使用代号为Inception的深度神经网络系统构建。
This paper by Google AI researchers describes their new object-detection system, GoogLeNet, built using a deep neural network system codenamed Inception.

类似于GoogleNet，这些残差模块一个接一个地堆叠，组成了完整的端到端网络。
Now similar to GoogleNet, these residual modules are stacked one over the other to form a complete end-to-end network.

这些深度学习模型-,澳门娱乐城;-包括GoogleNet和微软研究公司的ResNet--最初建立时的目的是从传统照片和视频信息中发现目标并进行分类。
The deep learning models, including GoogleNet and Microsoft Research's ResNet, were initially created to detect and classify objects in traditional photo and video imagery.

类似于GoogleNet，这些残差模块一个接一个地堆叠，组成了完整的端到端网络。
It is similar to GoogleNet in a way that residual models are placed one over the other to form a complete end-to-end network.

借助NeuralNetworkToolbox，您可以使用预先训练好的CNN模型（如GoogLeNet、AlexNet、vgg16、vgg19）以及Caffe和TensorFlow-Keras中的模型执行迁移学习。
With Deep Learning Toolbox, you can perform transfer learning with pretrained CNN models(such as GoogLeNet, AlexNet, vgg16, vgg19) and models from Caffe and TensorFlow-Keras.

GoogleNet本身没有短期劣势，但是该架构的进一步改变使模型性能更佳。
GoogleNet does not have an immediate disadvantage per se, but further changes in the architecture are proposed, which make the model perform better.

因此GoogLeNet设计了一个inception模块，使用普通的密集结构逼近一个稀疏CNN（如下图所示）。
So GoogLeNet devised a module called inception module that approximates a sparse CNN with a normal dense construction(shown in the figure).

GoogLeNet和它的后继者一度是ImageNet上最高效的模型之一，即在给定同样的测试精度下计算复杂度更低。
GoogLeNet, as well as its succeeding versions, was one of the most efficient models on ImageNet, providing similar test accuracy with lower computational complexity.