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For devices that interact with the physical world, it’s important to know not only what objects are in the vicinity, but also where they are

Apple wasn't the first to have a dual camera smartphone, but the company is the bellwether in this domain for driving mainstream features.

Additional in-depth resources focus on using various vision processor types for deep learning applications.

Convolutional neural networks (CNNs) and other deep learning techniques are one of the hottest topics in computer vision today.

With the growing popularity of CNNs, there’s a growing range of processor options being used to deploy these algorithms.

Applications like this have the potential to take Augmented Reality (AR) mainstream much faster than Virtual Reality (VR).

What functions will the cameras on board future cars perform, and where will they go?

By following in the footsteps of those who have come before you, you can gain valuable insights for use in your own development efforts.

Eye tracking is not new, but head mounted displays for virtual reality could be the catalyst technology needed to unlock its true potential.

CNNs and other deep learning techniques are rapidly becoming key enabling technologies for applications requiring object recognition, etc.