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.

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.

Computer vision can automate the process, extract that metadata about a video image and then store the metadata without the image. MORE FROM STATETECH: How is artificial intelligence being used in ...

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 ...

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 ...

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 ...

*Not like this robot-vision stuff is hard work by engineers, or anything. Efficiently solving multi-label MRFs (Readme) (C/C++ code) Segmentation, object category labelling, stereo Multi-label ...

Ubicept’s product is the signal processing and computer-vision algorithms that operate to interpret this ... that is when you run that same video through a computer vision object recognition ...

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 ...

Human-surveillance technologies have advanced in the past few years with the rapid development of artificial intelligence (AI ...