What is the translation of " 深度神经 " in English?

• deep neural

Examples of using 深度神经 in Chinese and their translations into English

实际上，他们的实验表明，深度神经网络在压缩阶段提高了泛化性能，在标记测试数据方面变得更好。
Indeed, their experiments revealed that deep neural networks ramp up their generalization performance during the compression phase, becoming better at labeling test data.

当深度神经网络在1980年代首次开发时，神经科学家希望这种系统可以用于对人脑建模。
When deep neural networks were first developed in the 1980s, neuroscientists hoped that such systems could be used to model the human brain.

NaftaliTishby最近在以色列领导的一项研究发现，深度神经网络会在每一层上有选择地丢弃非必要的信息。
Recent research in Israel led by Naftali Tishby has found that a deep neural network selectively drops non-essential information at each layer.

这使它可以配置深度神经网络，并且它与Java、Scala和其他JVM语言兼容。
It makes it possible to configure deep neural networks, and it's compatible with Java, Scala and other JVM languages.

深度神经网络具有大量隐藏层，有能力从数据中提取更加深层的特征。
Deep neural networks have a large number of hidden layers and are able to extract much deeper features from the data.

Cognata使用深度神经网络对各种传感器（包括相机，LiDAR和雷达）的精确行为进行准确建模。
Cognata uses Deep Neural Networks to accurately model the exact behavior of various sensors, including cameras, LiDAR, and Radar.

深度神经网络最大问题之一，尤其是不稳定的金融市场环境下，是过度拟合。
One of the biggest problems with deep neural networks, especially in the context of financial markets which are non-stationary, is overfitting.

深度学习或深度神经网络（DNN）框架涵盖具有许多隐藏层的各种神经网络拓扑。
A deep learning or deep neural network(DNN) framework covers a variety of neural network topologies with many hidden layers.

黑匣子(不透明)模型：深度神经网络、随机森林和梯度增强机器可以在此类别中考虑。
Black box(opaque) models: Deep neural networks, random forests, and gradient boosting machines can be considered in this category.

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.

MMdnn中的「MM」代表模型管理，「dnn」是「deepneuralnetwork」（深度神经网络）的缩写。
The‘MM' in MMdnn stands for model management and‘dnn' is an acronym for deep neural network.

在深度学习中，卷积神经网络（CNN或ConvNet）是一类深度神经网络，最常用于分析视觉图像。
In Deep Learning, a Convolutional Neural Network(CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery.

仅仅添加或删除几个像素就可以消除深度神经网络已经学会依赖的特定线索。
Adding or deleting just a few pixels can eliminate a particular cue that the deep neural network has learned to depend on.

AlphaGo不是一个纯粹的深度学习引擎，它结合了蒙特卡罗树搜索和至少两个深度神经网络。
AlphaGo wasn't a pure deep learning engine; it incorporated Monte Carlo Tree Search and at least two deep neural networks.

新的DeepLearningToolbox取代了NeuralNetworkToolbox，为工程师和科学家提供了用于设计和实现深度神经网络的框架。
The new Deep Learning Toolbox, which replaces Neural Network Toolbox, provides engineers and scientists with a framework for designing and implementing deep neural networks.

大多数深度学习方法使用神经网络架构，这也是深度学习模型通常被称为深度神经网络的原因。
Most deep learning methods use neural network architectures, which is why deep learning models are often referred to as deep neural networks.

在这篇文章中，你发现了使用Dropout正则化来减少过拟合，并改进深度神经网络的泛化。
In this post, you discovered the use of dropout regularization for reducing overfitting and improving the generalization of deep neural networks.

在深度学习中，卷积神经网络（CNN或ConvNet）是一类深度神经网络，最常用于分析视觉图像。
In deep learning, a convolutional neural network(CNN, or ConvNet) is a type of deep neural network, most commonly implemented to analysis of visual imagery.

Caffe已用于图像分类及其他视觉应用，支持基于GPU的加速度和NVIDIACUDA深度神经网络库。
Caffe has been used for image classification and other vision applications, and it supports GPU-based acceleration with the NVIDIA CUDA Deep Neural Network library.

到2017年，使用深度神经网络的参赛者将top5错误率降至3%以下。
By 2017, contestants using much deeper neural networks had pushed the top-five error rate down below three percent.

这使它可以配置深度神经网络，并且它与Java、Scala和其他JVM语言兼容。
Even the tool makes it possible to configure the deep neural networks and it is compatible with java, Scala and other JVM languages.

由于深度神经网络的工作方式不透明，所以要回答这个问题十分棘手。
Because of the opaque ways in which deep neural networks work, it's a tricky question to answer.

而包含长串规则的MLN可以表示深度神经网络，在规则串中，每层会有一个链接。
And an MLN with long chains of rules can represent a deep neural network, with one layer per link in the chain.

大多数深度学习系统都依赖于称为深度神经网络(DNN)的一种计算机体系结构。
Most deep learning systems rely on a type of computer architecture called a deep neural network(DNN).

虽然深度神经网络可以有效地从基于像素的图像中提取数字，但不能从其他信号中提取。
Although the deep neural network can effectively derive numbers from pixel-based images, it is not capable of doing so from other signals.

虽然Word2vec并不是深度神经网络，但它可以将文本转换为深度神经网络能够理解的数值形式。
While Word2vec is not a deep neural network, it turns text into a numerical form that deep nets can understand.

深度神经网络需要在庞大的数据集上进行训练，以使系统能够以最小的误差进行有效识别。
A deep neural network needs to be trained on a large dataset in order for the system recognize patterns effectively with minimal errors.

AlphaZero深度神经网络的参数，通过自我博弈的强化学习来训练，从随机初始化的参数开始。
The parameters θ of the deep neural network in AlphaZero are trained by reinforcement learning from self-play games, starting from randomly initialized parameters θ.

而最新发表在JournalsofGerontology期刊上的论文展示了深度神经网络在评估患者的生物学年龄上的应用。
The latest paper published in the Journals of Gerontology demonstrated the application of the deep neural networks to assessing the biological age of the patients.

Lanenet是一种深度神经网络，它使用一种类似于Enet的编码器-解码器架构，但经过了修改，具有两个分支。
Lanenet is a deep neural network that uses an encoder-decoder architecture similar to Enet, but modified to have two branches.