Computer software only recently became smart enough to recognize objects in photographs. Now, Stanford researchers using machine learning have created a system that takes the next step, writing a simple story of what’s happening in any digital image. At the heart of the Stanford system are algorithms that enable the system to improve its accuracy by scanning scene after scene, looking for patterns, then using the accumulation of previously described scenes to extrapolate what is being depicted in the next unknown image.
Automatic object recognition in images is currently tricky. Even if a computer has the help of smart algorithms and human assistants, it may not catch everything in a given scene. Google might change that soon, though; it just detailed a new detection system that can easily spot lots of objects in a scene, even if they’re partly obscured. The key is a neural network that can rapidly refine the criteria it’s looking for without requiring a lot of extra computing power.
A new scanning system at Six Flags sounds like it’s from the future, but the biometric scanner aims to make faster entrances for season pass holders. When guests arrive at the front gate for the first time of the season, they will present their voucher and a scanner processes an image of their fingerprint, assigning […]