Deep learning hasn't (yet) rendered classical computer vision obsolete. Why some challenges are still best solved with traditional algorithms. Skip to main content ...

Computer vision algorithms can check the identity of users, preventing identity theft and providing secure access to cryptocurrency accounts by examining facial features and ID papers. Automated ...

Computer vision is fundamental for a broad set of Internet of Things (IoT) applications. Household monitoring systems use cameras to provide family members with a view of what’s going on at home.

Deep learning finds numerous applications in machine vision solutions, particularly in enhancing image analysis and recognition tasks. Algorithmic models can be trained to recognize patterns ...

The present state of computer vision technology. Computer vision technology of today is powered by deep learning algorithms that use a special kind of neural networks, called convolutional neural ...

A brief history of computer vision. The earliest forms of machine vision system date back to the 1960s. Computer vision algorithms at that time were built to perform what are now considered to be ...

Because deep learning is the most general way to model a problem, it has the potential to solve difficult problems—such as computer vision and natural language processing—that outstrip both ...

Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural networ ...