Published on April 9th, 2019 | by Emergent Enterprise0
7 Amazing Examples Of Computer And Machine Vision In Practice
It is not hyperbole to say that artificial intelligence will change life as we know it. Just yesterday a new form of matter was discovered with the help of AI. And, of course, business is finding new ways to harness this technology such as with machine learning and computer vision. Bernard Marr at Forbes shares just a few ways that the enterprise is changing business with AI. Any business can evaluate an existing process or task and then determine if it makes sense for computers to “see” instead of humans in the process.
Photo Source: Adobe Stock
Even though early experiments in computer vision started in the 1950s and it was first put to use commercially to distinguish between typed and handwritten text by the 1970s, today the applications for computer vision have grown exponentially. By 2022, the computer vision and hardware market is expected to reach $48.6 billion. It is such a part of everyday life you likely experience computer vision regularly even if you don’t always recognize when and where the technology is deployed. Here is what computer vision is, how it works and seven amazing examples in practice today.
What is Computer Vision (CV)?
Computer vision is a form of artificial intelligence where computers can “see” the world, analyze visual data and then make decisions from it or gain understanding about the environment and situation. One of the driving factors behind the growth of computer vision is the amount of data we generate today that is then used to train and make computer vision better. Our world has countless images and videos from the built-in cameras of our mobile devices alone. But while images can include photos and videos, it can also mean data from thermal or infrared sensors and other sources. Along with a tremendous amount of visual data (more than 3 billion images are shared online every day), the computing power required to analyze the data is now accessible and more affordable. As the field of computer vision has grown with new hardware and algorithms so has the accuracy rates for object identification. In less than a decade, today’s systems have reached 99 percent accuracy from 50 percent making them more accurate than humans at quickly reacting to visual inputs.