在 英语 中使用 Deep-learning 的示例及其翻译为 中文
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Deep-learning will transform every single industry.
Their method involves building a deep-learning model that consists of multiple levels;
A deep-learning neural network recognizes objects in images using a simple trick.
Tech companies began frantically hiring all the deep-learning experts they could find.
We then design a deep-learning model as an alternative, and compare the two quantitatively.
人们也翻译
By 2009,researchers at the University of Toronto had shown that a many-layered deep-learning network could recognize speech with record accuracy.
To get a deep-learning system to recognize a hot dog, you might have to feed it 40 million pictures of hot dogs.
A team from Google demonstrated that deep-learning can diagnose eye disease in certain patients.
Deep-learning techniques use a large amount of known data to find a set of weights and bias values to match the expected results.
My research team is planning to build a deep-learning platform to understand massive amounts of multimedia data.
Using deep-learning techniques, the system can also provide a"sentiment score" for specific five-second intervals within a conversation.
Researchers at University of Adelaide have used deep-learning image analysis techniques to determine patient lifespans.
We believe deep-learning frameworks are like languages: Sure, many people speak English, but each language serves its own purpose.
I watched some of these systems operate in pilot demonstrations, but many of their features,especially the deep-learning components, are still in development.
Thrun insists that these deep-learning devices will not replace dermatologists and radiologists.
In response to these shortcomings, rebel researchers began advocating for artificial neural networks, or connectionist AI,the precursors of today's deep-learning systems.
For example, a dog-spotting deep-learning system doesn't understand that dogs typically have four legs, fur, and a wet nose.
Deep-learning systems are increasingly moving out of the lab into the real world, from piloting self-driving cars to mapping crime and diagnosing disease.
Researchers from NVIDIA have created a deep-learning system that can teach a robot, by merely observing a human's actions.
Built on top of a new mobile deep-learning platform called Caffe2Go, the feature lets users capture artistically stylized video footage in real-time.
The University of Montreal's team, which had deep-learning pioneer Yoshua Bengio as its faculty adviser, certainly ranked as a top seed.
A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.
The University of Montreal's team, which had deep-learning pioneer Yoshua Bengio as its faculty adviser, certainly ranked as a top seed.
All of this presumes, however, that deep-learning technology is viable for use in recruiting and human resources and could eventually become commonplace.
We can attempt to use the“knowledge” gained by another deep-learning model trained for a fairly similar task over a much larger amount of data.
For scientists and industry, deep-learning computers can search for potential drug candidates, map real neural networks in the brain or predict the functions of proteins.
Nvidia researchers have created a deep-learning system that can teach a robot simply by observing a human's actions.
The only data processing required for the deep-learning machine is to ensure the consistency of the image orientation and the voxel dimensions between images.
Their method involves building a deep-learning model that consists of several levels, each of which captures the relevant patterns of a specific temporal scale.
In the past year, it bought the deep-learning startup Nervana, the computer-vision chipmaker Movidius, and Mobileye, a supplier of assisted-driving systems.