What is the translation of " CONVOLUTIONAL " in Chinese?

• 卷积
• 一个卷积
• 神经

Examples of using Convolutional in English and their translations into Chinese

AlphaGo at its core is a convolutional neural network.
AlphaGo的核心是一个卷积神经网络。

Convolutional nets are inspired by the visual system's structure.
卷积神经网络受视觉系统的结构启发而产生。

Technically, AlexNet was a convolutional neural network.
从技术上讲，AlexNet是一个卷积神经网络。

Convolutional Neural Networksnavigate_next Convolutional Neural Networks.
卷积神经navigate_next卷积神经网络.

Conv2D is a class that we will use to create a convolutional layer.
Conv2D是用于创建卷积层的类。

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。

As iOS 10 had few basic kernels for creating convolutional networks.
但是iOS10只提供了几个用于创建神经网络的基本kernel。

Convolutional Filters learn good representations automatically, without needing to represent the whole vocabulary.
卷积滤波器自动学习良好的表示，而无需表示整个词汇表。

For example, consider the following 3x3 convolutional filter:.
以下面的3x3卷积过滤器为例：.

But if you have a convolutional neural network and you're doing a 17 x 17 multiplier, that may be overkill.
但如果你有一个卷积神经网络并且要做一个17×17的乘法器，那可能就有点过头了。

To turn one layer into two layers, we use convolutional filters.
为了将一层转换为两层，我们需要使用卷积滤波器。

We trained a convolutional neural network(CNN) to predict the probability that a given Kepler signal is caused by a planet.
我们训练了一个卷积神经网络(CNN)来预测给定开普勒信号由行星引起的可能性。

We repeat this procedure for all the convolutional layers in the network.
我们对网络中所有的卷积层都重复这一过程。

In the leading object detection method R-CNN[7], the features from candidate windows are extracted via deep convolutional networks.[…].
目前领先的方法是R-CNN[7]，候选窗口的特征是借助深度神经网络进行抽取的。

A particularly powerful characteristic of these convolutional filters is their positional invariance.
这些卷积滤波器的一个特别强大的特性是它们的位置不变性。

In order to make up for the information lost upon pooling, we will typically increase the number of filters in subsequent convolutional layers.
为了弥补集中丢失的信息，我们通常会增加后续卷积层中的滤波器数量。

Semantic image segmentation with deep convolutional nets and fully connected CRFs, L. Chen et al.[pdf].
使用深度卷积网和完全连接的CRF进行语义图像分割，L.Chen等.[[PDF]]（WEB.

But iOS 10 only provided a few basic kernels for creating convolutional networks.
但是iOS10只提供了几个用于创建神经网络的基本kernel。

The system uses a machine learning model called a convolutional neural network(CNN), commonly used for image recognition.
该系统使用称为卷积神经网络(CNN)的机器学习模型，通常用于图像识别。

A convolutional neural network wins the German Traffic Sign Recognition competition with 99.46% accuracy(vs. humans at 99.22%).
卷积神经网络赢得了德国交通标志识别竞赛，识别准确率为99.46％（人类最高准确率是99.22％）。

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：.

A convolutional network is composed of one or more convolutional layers(filtering layers), followed by a fully connected multilayer neural network.
一个卷积网络由一个或多个卷积层（过滤层）组成，然后是一个完全连接的多层神经网络。

Error-correcting codes are usually distinguished between convolutional codes and block codes:.
纠错码经常区分为convolutionalcodes与blockcodes：.

Internal data representation of a convolutional neural network does not take into account important spatial hierarchies between simple and complex objects.
卷积神经网络的内部数据表示不考虑简单和复杂对象之间的重要的空间层次结构。

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。

Thanks to convolutional neural networks, not only can computers tell the difference between cats and dogs, they can even recognise different breeds of dogs.".
多亏了卷积神经网络，计算机不仅能够分辨猫和狗之间的区别，还能够识别不同品种的狗。

Our key insight is to build"fully convolutional" networks that take input of arbitrary size and produce correspondingly-sized output with efficient inference and learning.
我们的核心观点是建立“全卷积”网络，输入任意尺寸，经过有效的推理和学习产生相应尺寸的输出。

Task-Driven Convolutional Recurrent Models of the Visual System can simultaneously perform machine vision tasks and explain the dynamics of the monkey's visual system.
任务驱动的视觉系统卷积循环模型可以同时执行机器视觉任务并解释猴子视觉系统的动态.

In particular, the continuous-filter convolutional network SchNet accurately predicts chemical properties across compositional and configurational space on a variety of datasets.
特别是，连续滤波器卷积网络SchNet准确地预测了各种数据集上的组成和配置空间的化学特性。

In Deep Learning, a Convolutional Neural Network(CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery.
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。