A study examining the brain of a person with object agnosia, a defect in the inability to recognize objects, is providing a unique window into the sophisticated brain mechanisms critical for object ...

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 research team led by Masakazu Ohara, graduate student of the Department of Computer Science and Engineering at Toyohashi University of Technology (student in the Leading Program doctoral program); ...

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 ...

If we've learned anything from post-apocalyptic movies it's that computers eventually become self-aware and try to eliminate humans. One engineer isn't interested in that development, but he has ...

Near-infrared (NIR) photon detection and object recognition are crucial technologies for all-weather target identification. Conventional NIR detection systems that rely on photodetectors and von ...

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.

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 ...