CAFFE in English translation

Examples of using Caffe in Chinese and their translations into English

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Caffe的一个重要特色是可以在不编写代码的情况下训练和部署模型。!
An important distinctive feature of Caffe is that one can train and deploy models without writing any code!
如果对我们的实验加以总结,那就是使用Caffe的SSD训练时间远远多于使用MXNet的训练时间。
To summarize our experiments, training time for SSD with Caffe is far higher than with the MXNet implementation.
使用Caffe训练时nvidia-smi的输出,使用的批处理大小16。
Output of nvidia-smi while training with Caffe, using a batch size of 16.
使用Caffe,你可以轻易地构建一个用于图像分类的CNN(卷积神经网络)。
With Caffe, you can very easily build a convolutional neural network(CNN) for image classification.
使用Caffe训练时nvidia-smi的输出,使用的批处理大小8。
Output of nvidia-smi when training with Caffe, using a batch size of 8.
利用Caffe,您能够非常轻松地构建起卷积神经网络(简称CNN)以实现图像分类。
With Caffe, you can very easily build a convolutional neural network(CNN) for image classification.
网络拓扑结构基于Caffe中提供的内置示例,具有三个卷积层和一个完全连接层。
The network topology is based on the built-in example provided in Caffe, with three convolution layers and one fully-connected layer.
Caffe为例,你可以通过连接不同类型的「层(layer)」来设计神经网络。
With Caffe for example, you design a neural network by connecting different kinds of“layers”.
我记得,从这个网页上看到这个特殊实现使用了Caffe框架。
And it looks like from what I remember seeing from this webpage, this particular implementation uses the Cafe framework.
在AWS,我们非常开放,支持所有深度学习框架,如从ApacheMXNet到TensorFlow到Caffe到Theano等等。
At AWS we are very open about supporting all deep learning frameworks like from Apache MXNet to TensorFlow to Caffe to Theano and more.
此外,额外的关键词对于区分不同框架而言是非常有必要的,因为我最初还尝试在这个分析中加入Caffe库。
An additional keyword was necessary to differentiate that framework from unrelated terms because I was originally planning to include the Caffe library in this analysis.
Caffe与Caffe2彼此分离,因此数据科学家可继续使用Caffe
Caffe and Caffe2 are separate repos, so data scientists can continue to use the orginial Caffe.
像TensorFlow、PyTorch、Caffe、MXNet和Chainer这样的深度学习框架减少了训练和使用深度学习模型所需的工作量和技能。
Deep learning frameworks like TensorFlow, PyTorch, Caffe, MXNet, and Chainer have reduced the effort and skills needed to train and use deep learning models.
Caffe于2017年发布,是一家小巧的机器学习框架,面向专注于速度、模块化和表现力的人工智能开发公司。
Caffe, released in 2017, is known as a smaller machine learning framework for an artificial intelligence development company focusing on speed, modularity, and expressiveness.
CAFFE是由伯克利视觉与学习中心开发的一个深度学习框架。
Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center.
CAFFE是一个用于深度学习的开源库,由伯克利视觉和学习中心开发。
Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center.
Caffe已经被Caffe2取代.
Caffe has yet to be replaced by Caffe2.
CaffeGreco来罗马最老的咖啡厅.
Caffe Greco sits as Rome's oldest and most famous cafe.
Caffe是一个深度学习框架。
Caffe machine learning is a deep learning framework.
Caffe是一个深度学习框架。
Caffe is a deep learning framework.
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