Examples of using A neural network in English and their translations into Vietnamese
{-}
-
Colloquial
-
Ecclesiastic
-
Computer
In this example, we consider it to use a neural network system with one hidden layer.
it took 1,000 devices with 16,000 CPUs to simulate a neural network.
Using a dataset of millions of videos on YouTube, the researchers trained an AI based on a neural network model called Speech2Face.
There is a certain danger in using a neural network: if it is wrongly trained, it can cause a lot of damage.
Nathanial Rochester from the IBM research laboratories led the first effort to simulate a neural network.
Our crew has created a neural network capable of learning based on the knowledge and experience of professional traders.
Use of a support vector regression or a neural network would make the resultant Quality Scores nigh impossible to thoroughly reverse-engineer because it is holistic.
A neural network has been out since the nineties with the seminal paper of Yann LeCun.
Encog, a neural network and artificial intelligence framework available for Java,. Net, and Silverlight.
A neural network based localization algorithm will locate the location of the license plate.
then fed them into a neural network.
Learning rate is one of the parameters which governs how fast a neural network learns and how effective the training is.
As a result, the mega-image is divided into tens of thousands of smaller individual images so that a neural network can analyze each of them separately.
FAIR becomes the first AI research team to create an unsupervised learning method for recreating high-fidelity music with a neural network.
The term"dropout" refers to dropping out units(both hidden and visible) in a neural network.
The term“dropout” refers to dropping out units(hidden and visible) in a neural network.
people noticed that in a neural network with a relatively large number of layers, it was common
We have introduced the Neural Turing Machine, a neural network architecture that takes inspiration from both models of biological working memory and the design of digital computers,” the research team wrote.
Researchers then built a neural network to process the results and distinguish the signal from the noise that the sensors were collecting,