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This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.
Ben Dickson, founder of TechTalks summarizes, Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do.
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| Photo: JumpStory |
In recent years, computer vision has taken great leaps thanks to advances in deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.
These advances have paved the way for boosting the use of computer vision in existing domains and introducing it to new ones. In many cases, computer vision algorithms have become a very important component of the applications we use every day...
Image editing and enhancement Many companies are now using machine learning to provide automated enhancements to photos. Google’s line of Pixel phones use on-device neural networks to make automatic enhancement such as white balancing and add effects such as blurring the background.
Another remarkable improvement that advances in computer vision have ushered in is smart zooming. Traditional zooming features usually make images blurry because they fill the enlarged areas by interpolating between pixels. Instead of enlarging pixels, computer vision-based zooming focuses on features such as edges, patterns. This approach results in crisper images.
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Source: The Next Web
