The CEVA-XM4– CEVA’s most recent vision and imaging platform- builds on the combination of vision algorithm expertise and core architecture know-how and provides a well-tuned vision processor to ...

Caltech's database is used to benchmark the algorithm against other similar research, with other "published well-performing object recognition systems" scoring 95-98 percent accuracy in the same ...

Computer vision algorithms are analyzing medical images, enabling self-driving cars, and powering face recognition. But training models to recognize actions in videos has grown increasingly expensive.

Its performance should thus continue to improve as computer-vision researchers develop better recognition software, ... Despite working with existing SLAM and object-recognition algorithms, ...

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 ...

So, computer vision in smart transportation can resolve this through object detection and name recognition for such vehicles. The machine learning algorithms can identify the vehicle and its ...

It uses computer vision and image recognition to make its judgments. It may not seem impressive, after all a small child can tell you whether something is a hotdog or not.

A team of researchers at MIT CSAIL, in collaboration with Cornell University and Microsoft, have developed STEGO, an algorithm able to identify images down to the individual pixel.

Object recognition: Finding the boundaries between objects helps segment images, ... Computer vision algorithms provide a good way to ensure quality control and improve safety, ...

AI image recognition has made some stunning advances, but as new research shows, the systems can still be tripped up by examples that would never fool a person. Labsix, a group of MIT students who ...