Examples of using Artificial neural networks in English and their translations into Vietnamese
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Artificial neural networks.
Researcher and developer of artificial neural networks.
Artificial neural networks are extremely good and getting better and better in these fields.
A new generation of chatbot has been born- artificial neural networks that recognize patterns in speech.
Artificial neural networks, as they are called, remained an impractical technology for decades.
In fact,deep learning is a version of a group of algorithms called artificial neural networks(NN).
This article is a part of Artificial Neural Networks Series, which you can check out here.
Recent successes in machine learning are based on analogies with animal brains,i.e. artificial neural networks;
Previously obscure, artificial neural networks were the talk of Silicon Valley.
Joone is a FREE Neural Network framework to create,train and test artificial neural networks.
This isn't to say that artificial neural networks are better than conventional computers.
You can learn about other classification algorithms, like naive Bayes,k-nearest neighbor, and artificial neural networks.
Applying artificial neural networks to predict carbon dioxide(CO2) corrosion rate in oil and gas pipeline(42%).
Another algorithmic approach from the early machine-learning crowd, artificial neural networks, came and mostly went over the decades.
Much work in what is called metalearning or learning to learn, including Google's,is aimed at speeding up the process of deploying artificial neural networks.
Conventional software operates within strict parameters but artificial neural networks have the ability to“learn” by being fed more and more data over time.
On the technical side, in addition to computational hydraulics, hydroinformatics has a strong interest in the use of techniques originatingin the so-called artificial intelligence community, such as artificial neural networks or recently support vector machines and genetic programming.
One is to invent new chips to run artificial neural networks, the form of software propelling the AI ambitions of Google and other tech companies.
Where the nervous system uses biological synapses to process chemical andelectrical signals, artificial neural networks use synthetic synapses to process digital information.
Although the field of computer science reject the Artificial Neural Networks after the publication of the book"Perceptrons" by Minsky and Papert, but scientists are still studying the art of another perspective, namely physics.
How It Will Work: During the two-year program, researchers will record motor and sensory signals from the spinal cord anduse artificial neural networks to learn how to stimulate the post-injury site to communicate motor commands.
The key is to train artificial neural networks to recognize the underlying structure of the images in order to fill in views omitted from the accelerated scan,» Facebook wrote in the blog post.
Other Deep Learning working architectures, specifically those built from artificial neural networks(ANN), date back to the Neocognitron introduced by Kunihiko Fukushima in 1980.
In the manufacturing sector, Artificial Neural Networks are proving to be an extremely effective Unsupervised learning tool for a variety of applications including production process simulation and Predictive Quality Analytics.
The Russian Kalashnikov arms manufacturer has developed afully automated combat module based on artificial neural networks, which allows it to identify targets, learn and make decisions on its own.
Developed by the Google Brain team,'artificial neural networks'(much like those in our skulls) are offering an alternative to traditional computer programming and represent a move towards self-learning machines.
This ability to process a largenumber of parameters through multiple layers makes Artificial Neural Networks very suitable for the variable-rich and constantly changing processes common to manufacturing.
Skychain believes its diagnostics system- a“distributed open network” of artificial neural networks(or ANNs for short)- can identify conditions in patients and prescribe appropriate treatments in milliseconds, substantially reducing the risk of human error during the crucial diagnosis stage.
Deep learning architectures, specifically those built from artificial neural networks(ANN), date back at least to the Neocognitron introduced by Kunihiko Fukushima in 1980.