Recently a group of Google engineers took top score in a number of categories at the annual ImageNet 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.
The technology is still in its infancy 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, the tech could be a major part of visual search engines and other image related user services. A recent Google Research blog post 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.”