Scientists at Brigham Young University (BYU) have developed an algorithm that can accurately identify objects in images or videos and can learn to recognize new objects on its own.

BYU engineer Dah-Jye Lee isn’t interested in that development, but he has managed to eliminate the need for humans in the field of object recognition. Lee has created an algorithm that can accurately ...

The BYU algorithm tested as well or better than other top object recognition algorithms to be published, including those developed by NYU's Rob Fergus and Thomas Serre of Brown University.

In December, CSAIL researchers will present a new way of using machine learning at the annual Conference on Neural Information Processing Systems. Built on a new object-recognition algorithm, this ...

WiMi's 3D object recognition system based on multi-view feature fusion consists of three main parts: viewpoint information selection, feature extraction, and feature fusion.

In high-risk industry work scenarios, automatic hard hat recognition systems are crucial for ensuring worker safety. However, the issue of false detection has become a 'stumbling block' affecting ...

Helping robots recognize common objects may bring household robot help one step closer. MIT researchers develop computer algorithm that can help such a robot quickly identify objects it would need ...

Then they'll run a recognition algorithm on just the pixels inside each rectangle. To get a good result, a classical object-recognition system may have to redraw those rectangles thousands of times.

Object detection and recognition are an integral part of computer vision systems. In computer vision, the work begins with a breakdown of the scene into components that a computer can see and analyse.

Smart object recognition algorithm doesn't need humans Date: January 16, 2014 Source: Brigham Young University Summary: If we've learned anything from post-apocalyptic movies it's that computers ...