Oleg Zabluda's blog
Thursday, September 15, 2016
 
"""
"""
Gaidon and colleagues used a popular game development engine, called Unity, to generate virtual scenes for training deep-learning algorithms [...] to recognize objects and situations in real images.
"""
https://www.technologyreview.com/s/601009/to-get-truly-smart-ai-might-need-to-play-more-video-games/

"""
off-the-shelf computer games, [...] photorealistic imagery [...] A team of researchers from Intel Labs and Darmstadt University in Germany has developed a clever way to extract useful training data from Grand Theft Auto. [...] created a software layer that sits between the game and a computer’s hardware, automatically classifying different objects in the road scenes shown in the game. [...] it would be nearly impossible to have people label all of the scenes with similar detail manually. The researchers also say that real training images can be improved with the addition of some synthetic imagery. [...] It takes thousands of hours to collect real street imagery, and thousands more to label all of those images. It’s also impractical to go through every possible scenario in real life, like crashing a car into a brick wall at a high speed.
"""
https://www.technologyreview.com/s/602317/self-driving-cars-can-learn-a-lot-by-playing-grand-theft-auto/
https://www.technologyreview.com/s/602317/self-driving-cars-can-learn-a-lot-by-playing-grand-theft-auto

Labels:


- posted by Oleg Zabluda @ 8:33 PM | permalink | | | technorati | bloglines | feedster
| |

Home

Powered by Blogger