What is the translation of " 人工神经网络 " in English?

• artificial neural network
• artificial neural networks
• anns

Examples of using 人工神经网络 in Chinese and their translations into English

人工神经网络能够学习，而且它们需要训练。
The artificial neural network is capable of learning and they need to be trained.

人工神经网络方法较回归模型预测误差较小。
The artificial neural network method has less prediction error than the regression model.

人工神经网络语音识别和电脑视觉[13].
An artificial neural network for speech recognition and computer vision[17].

研究人员正试图建立人工神经网络，可以适当地适应新的信息，而不会突然忘记他们以前学过的东西。
Researchers are trying to build artificial neural networks that can appropriately adjust to new information without abruptly forgetting what they learned before.

这些人工神经网络通常需要大量的计算能力才能处理数百万个参数并执行指定任务。
These ANNs often require serious computational power to crunch through millions of parameters to perform a designated task.

凭借其广泛的库，你可以在人工神经网络，统计数据处理，图像处理等中构建各种应用。
With its extensive range of libraries, you can build various applications in artificial neural networks, statistical data processing, image processing, and many others.

人工神经网络可以揭示大量基因表达数据中的模式，并发现与疾病相关的基因组。
An artificial neural network can reveal patterns in huge amounts of gene expression data, and discover groups of disease-related genes.

随着学习问题在规模和复杂性方面的增长，并扩展到多学科领域，将需要用于缩放人工神经网络的模块化方法。
As learning problems grow in scale and complexity, and expand into multi-disciplinary territory, a more modular approach for scaling ANNs will be needed.

例如，生物合理深/复发人工神经网络的学习来解决，只有10年前似乎是不可行的模式识别任务。
For example, biologically plausible deep/recurrent artificial neural networks are learning to solve pattern recognition tasks that seemed infeasible only 10 years ago.

人工神经网络模型有一个属性，称为“容量”，这大致相当于他们可以塑造任何函数的能力。
Artificial neural network models have a property called'capacity', which roughly corresponds to their ability to model any given function.

麦卡洛特和皮茨发展了我们今天称为人工神经网络的最早版本，来源于生物神经网络结构的计算模型。
McCulloch and Pitts developed the first variants of what are now known as artificial neural networks, models of computation inspired by the structure of biological neural networks..

尽管体积巨大，成功的深度人工神经网络在训练和测试性能之间可以展现出非常小的差异。
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance.

该人工神经网络可以说从几个样本（标注数据）和其错误（误差传播）中得到了学习。
This artificial neural network is said to have learned from several examples(labeled receipts) and from its mistakes(error propagation).

与此同时，人工神经网络依然是个“黑箱子”，可解释性比较差。
At the same time, artificial neural network is still a“black box”, the interpretation is relatively poor.

人工神经网络是模仿人类大脑和神经系统的计算机系统，而深度学习也是AI进步的原因。
Artificial neural networks, which are computer systems modeled on the human brain and nervous system, and deep learning are also responsible for advances in AI.

今年，中国大洋协会将就模糊逻辑和人工神经网络技术开展工作，以便提供关于无数据生态区的资料。
During the year, COMRA will work on fuzzy logic and artificial neural network techniques to provide information on areas with no data.

现代人工神经网络由一系列软件组成，分为输入、隐藏层和输出几个部分。
Modern artificial neural networks are composed of an array of software components, divided into inputs, hidden layers and outputs.

自动编码器是一种类型的人工神经网络用于学习高效的数据值编码以无监督方式。
An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner.

研究人员正试图建立人工神经网络，以便在突然忘记之前学过的东西的情况下，适当地调整新信息。
Researchers are trying to build artificial neural networks that can appropriately adjust to new information without abruptly forgetting what they learned before.

大多数人工神经网络有两个共同点:大量的权值，本质上是网络在训练中学习的可调参数;
Most artificial neural networks have two things in common: a huge number of weights, which are essentially the tunable parameters that networks learn during training;

第一个人工神经网络(ANN)Perceptron早在1958年即由心理学家FrankRosenblatt发明出来。
The first artificial neural network(ANN)- Perceptron- was invented in 1958 by psychologist Frank Rosenblatt.

它们也被称为移位不变或空间不变人工神经网络（SIANN），基于它们的共享权重架构和平移不变性特征。
They are also known as shift invariant or space invariant artificial neural networks(SIANN), based on their shared-weights architecture and translation invariance characteristics.

同时，他还发布了开源人工神经网络软件（NICOToolkit），并在全球收获了数千名研究人员的下载。
He also published Open Source Artificial Neural Network software(The NICO Toolkit), which has been downloaded by thousands of researchers worldwide.

人工神经网络分析并了解了该设备生成的高质量图像的特征。
An artificial neural network analyzed and learned the features of the superior-quality images that were generated by this device.

人工神经网络倾向于模拟人类的神经系统和大脑功能，它的知识来源于物理、生物和神经科学。
Artificial neural networks tend to simulate the human nervous system and brain functions, deriving its knowledge from physics, biology, and neuroscience.

这些人已经表明，生物系统用来学习和遗忘的方法也可以与人工神经网络一起工作。
These guys have shown that the approach biological systems use to learn, and to forget, can work with artificial neural networks too.

这是一种人工神经网络，用于无监督学习有效地编码。
It is an artificial neural network used for unsupervised learning of efficient codings.

在神经生物学的启发下，机器学习的改进导致人工神经网络接近或偶尔超越了人类（1,2）。
Refinements in machine learning, inspired by neurobiology, have led to artificial neural networks that approach or, occasionally, surpass humans(1, 2).

人工神经网络的氮，磷，溶解氧浓度模型在非点源浙江省东南…污染的河流;
Artificial neural network modelling of concentrations of nitrogen, phosphorus and dissolved oxygen in a non-point source polluted river in Zhejiang Province, southeast….

为了克服这些苛刻的限制，研究人员利用人工神经网络(ANN)从量子力学中学习原子间的相互作用。
In order to avoid such harsh limitations, scientists have now used an artificial neural network(ANN) to learn the atomic interactions from quantum mechanics.