What is the translation of " INCEPTION " in English?

• inception

Examples of using Inception in Chinese and their translations into English

Inception真的是非常强大。
The opening is really strong.

他和他的团队提出了Inception模块：.
He and his team came up with the Inception module:.

Inception的每一刻都是梦境。
Every single moment of Inception is a dream.

它对应Inception块中的第二线路。
This corresponds to the second path in the Inception block.

Inception模块现在有多个更新版本（版本6和7）。
There are updated versions to the Inception module(Versions 6 and 7).

它对应Inception块中的第二条线路。
This corresponds to the second path in the Inception block.

一家公司叫ForeverSpin甚至重新创建了Inception顶部。
(A company called ForeverSpin has even recreated the Inception top.).

首先，我们必须调整图像的大小，使之适应Inception模型。
First, we have to resize the image to fit into the Inception model.

Inception模块允许你做的是并行执行所有这些操作。
What an Inception module permits you to do is perform all these operations in parallel.

这样，我们就使用Inception模型的最后一层得到了1024个单元。
This way, we get 1024 rows with the final layer from the Inception model.

Inception的作者对训练更大型网络的计算效率尤其感兴趣。
In particular, the authors of Inception were interested in the computational efficiency of training larger nets.

换句话说，对于每一个层，Inception都会执行5×5卷积变换、3×3卷积变换和最大池化。
In other words, for each layer, Inception does a 5×5 convolutional transformation, and a 3×3, and a max-pool.

在我们开始使用Inception的时候，我重新进行了2001年的测试，并且在这些设置和风格上有一些相似之处。
I rewatched 2001 around the time we did Inception, and there are some similarities in the sets and the style.

对于那些在家里算的人来说，Inception是DiCaprio疯狂的妻子突然死去的第三部电影。
For those of you counting at home, Inception is the third movie in a row in which DiCaprio's crazy wife suddenly dies.

引入了“Inception单元”，强调了卷积神经网络的层不需要每次都按照顺序排列叠加。
Introduced the Inception Module, which emphasized that the layers of a CNN doesn't always have to be stacked up sequentially.

为了解决上述计算瓶颈，Inception的作者使用了1×1卷积来「过滤」输出的深度。
In order to solve the computational bottleneck, the authors of Inception used 1×1 convolutions to“filter” the depth of the outputs.

年3月，赛门铁克对InceptionFramework组织滥用易受攻击的UPnP服务来隐藏攻击行为的事件进行了报道。
In March 2018, Symantec reported about the Inception Framework abusing vulnerable UPnP services to hide themselves.

使用分布式训练，我们训练了生成网络（InceptionNetwork），在100个GPUs和不到65小时的训练时间下，达到了78%的正确率。
Using the distributed trainer, we trained the Inception network to 78% accuracy in less than 65 hours using 100 GPUs.

自带有一些预处理的数据集和经过训练的模型，包括：MNIST、VGG、Inception、SqueezeNet、以及ResNet等。
It comes with several pre-processed datasets and trained models including, MNIST, VGG, Inception, SqueezeNet, ResNet, etc.

最新的版本Inceptionv4甚至将残差连接放进了每一个模组中，创造出了一种Inception-ResNet混合结构。
The latest version of Inception, v4, even threw in residual connections within each module, creating an Inception-ResNet hybrid.

现在,一个新的服务已经登陆各个平台,他们希望可以成为虚拟现实中的Netflix,这个服务的名字叫Inception。
Now a new service is available across multiple platforms that wants to become the Netflix of virtual reality(VR), called Inception.

这能达到多好的效果？Inception的第一个版本是GoogLeNet，也就是前面提及的赢得了ILSVRC2014比赛的22层网络。
The first version of Inception, dubbed“GoogLeNet,” was the 22-layer winner of the ILSVRC 2014 competition I mentioned earlier.

Inception表示新资金将有助于Inception扩大其内容范围，提升其技术平台水平并加速经济增长。
Inception said that the funding will help the company to expand its content catalogue, enhance its technology platform and accelerate growth.

我想使用迁移学习：采用Inception，这是Google当时最好的图像分类架构，然后使用我的癌症数据重新进行训练。
I wanted to use transfer learning: take Inception, Google's best image classification architecture at the time, and retrain it on my cancer data.

Inception是一个沉浸式内容平台，于2016年10月推出，旨在为VR用户提供各种高质量的内容。
Inception is an immersive content network which was launched in October 2016 in order to offer a diverse range of high-quality content to VR users.

另外注意到图中inception区块被简化了，比先前的InceptionV3种要包含更少的并行塔（paralleltowers）。
Here, notice that the inception blocks have been simplified, containing fewer parallel towers than the previous Inception V3.

Inception同时在与地下音乐粉丝社区BoilerRoom合作,为社区现场音乐活动制作一个专门的频道。
Inception has also partnered with Boiler Room, a community of underground music fans, to create a dedicated channel for the communities live music events.

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.

模型一直在被改善，每次都能达到当前最高水准的结果：QuocNet，AlexNet，Inception（GoogLeNet），BN-Inception-v2。
Successive models continue to show improvements, each time achieving a new state-of-the-art result: QuocNet, AlexNet, Inception(GoogLeNet), BN-Inception-v2.