Difference between revisions of "User:RahalMccall69"
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| − | + | Recently a group of Google engineers in a number of categories at the annual ImageNet <a href=http://www.aec-ist.com/css/Cheap-Gucci-Handbags-Suits-Pants-Beanie.html>Cheap Gucci Handbags</a> computer vision competition for their work with automatic image detection. The researchers have developed a new detection technology that can automatically identify large numbers of objects within an image with much greater accuracy than previous systems. | |
| + | The system can identify large numbers of objects within a given image, even when partially obscured, using something called a neural network. This AI network allows the system to constantly be switching between search criteria, allowing for much better item identification without the need for a massive amount of computing power. Based on the example above given by Google, it can track a TV monitor, two small domestic cats (one on the floor, one mid-jump) as well as a partially obstructed bookshelf and other things in a single image. | ||
| + | The technology is still in its infancy <a href=http://www.aec-ist.com/css/Gucci-Outlet-Online-Flats-Cufflinks-Bookbags.html>Gucci Outlet Online</a> but many suggest it could have major implications with self driven cars and other automated robotic services in the future. On a more immediate basis, <a href=http://www.aec-ist.com/css/Gucci-Discount-Scarf-Sale-Uk-Satchel.html>Gucci Scarf Sale</a> the tech could be a major part of visual search engines and other image related user services. A recent said these technological advances are directly transferable to Google products such as photo search, image search, YouTube, self-driving cars, and any place where it is useful to understand what is in an image as well as where things are. | ||
Revision as of 02:42, 2 October 2014
@@@ Recently a group of Google engineers in a number of categories at the annual ImageNet <a href=http://www.aec-ist.com/css/Cheap-Gucci-Handbags-Suits-Pants-Beanie.html>Cheap Gucci Handbags</a> computer vision competition for their work with automatic image detection. The researchers have developed a new detection technology that can automatically identify large numbers of objects within an image with much greater accuracy than previous systems. The system can identify large numbers of objects within a given image, even when partially obscured, using something called a neural network. This AI network allows the system to constantly be switching between search criteria, allowing for much better item identification without the need for a massive amount of computing power. Based on the example above given by Google, it can track a TV monitor, two small domestic cats (one on the floor, one mid-jump) as well as a partially obstructed bookshelf and other things in a single image. The technology is still in its infancy <a href=http://www.aec-ist.com/css/Gucci-Outlet-Online-Flats-Cufflinks-Bookbags.html>Gucci Outlet Online</a> but many suggest it could have major implications with self driven cars and other automated robotic services in the future. On a more immediate basis, <a href=http://www.aec-ist.com/css/Gucci-Discount-Scarf-Sale-Uk-Satchel.html>Gucci Scarf Sale</a> the tech could be a major part of visual search engines and other image related user services. A recent said these technological advances are directly transferable to Google products such as photo search, image search, YouTube, self-driving cars, and any place where it is useful to understand what is in an image as well as where things are.