Before deep learning, creating computer vision algorithms that could process medical images required extensive efforts from software engineers and subject matter experts.

Researchers say they've found evidence of pervasive bias in computer vision algorithms trained on ImageNet, a popular photo dataset.

Agencies are interested in using computer vision to enhance their missions and improve security. But what is computer vision technology, and how can feds use it? An interior view of the atrium in the ...

A computer-implemented method for processing a video feed of a user performing a diagnostic test using a set of stacked computer vision algorithms, the method comprising: receiving, from a user ...

Over the past decades, computer scientists have developed increasingly sophisticated sensors and machine learning algorithms ...

Computer vision algorithms can detect anomalies and predict outcomes, even estimating treatment costs based on jaw images. Computer vision aids in surgery by converting broken bone MRIs into 3D ...

Researchers have shrunk state-of-the-art computer vision models to run on low-power devices. Growing pains: Visual recognition is deep learning’s strongest skill. Computer vision algorithms are ...

Computer vision algorithms can inherit biases present in training data, leading to biased or unfair outcomes.

Circle detection algorithms form a fundamental pillar in computer vision, enabling the identification of circular features across a wide range of applications from automated industrial inspection ...

In the operating room, Artisight's smart hospital platform can now autonomously detect and document patient entry and exit, procedure start and end time, and other key milestones in a patient ...

What computer vision algorithms bring to the table is the scalability and aptitude to memorize outcomes. Instead of capturing and storing large amounts of video data, computer systems can, for example ...