In the blink of an eye, the human visual system can process an object, determining whether it's a cup or a sock within milliseconds, and with seemingly little effort. It's well-established that an ...

Object recognition is one of the core topics in computer vision research: After all, a computer that can see isn't much use if it has no idea what it's looking at. Researchers have developed new ...

Imagine waiting for incoming passengers at the arrival gate at the airport. Your visual system can easily find faces and identify whether one of them is your friend's. As with other tasks that our ...

Neuroscientists at Johns Hopkins University (JHU) have discovered how we see objects in depth. Even if computers are better than humans in chess games, they can't beat us in the field of object ...

Fig. 1. Design and fabrication of a multiphoton neuron tactile skin. (a) The design concept and spatial reconstruction workflow of the multiphotonic neuron haptic skin for simulating the tactile ...

The automatic recognition of 3D objects with "uncooperative" surfaces is a difficult and slow process. The Fraunhofer IOF has a solution. The Fraunhofer Institute for Applied Optics and Precision ...

To researchers’ surprise, deep learning vision algorithms often fail at classifying images because they mostly take cues from textures, not shapes. When you look at a photograph of a cat, chances are ...

What if you could teach a computer to recognize a zebra without ever showing it one? Imagine a world where object detection isn’t bound by the limits of endless training data or high-powered hardware.

Josh Lowensohn joined CNET in 2006 and now covers Apple. Before that, Josh wrote about everything from new Web start-ups, to remote-controlled robots that watch your house. Prior to joining CNET, Josh ...

Most people’s drawing skills peaked in first grade. Which means the diagrams we include in handwritten notes often look like they were drawn by a moderately skilled raccoon. Fortunately, iPadOS 14 ...