These annotations played a critical role in enhancing the precision of YOLOv8, the deep learning model the researchers trained, by allowing it to better detect subtle differences in hand gestures.

American Sign Language (ASL) recognition systems often struggle with accuracy due to similar gestures, poor image quality and inconsistent lighting. To address this, researchers developed a system ...

Millions of people communicate using sign language, but so far projects to capture its complex gestures and translate them to verbal speech have had limited success. A new advance in real-time ...

That data could also enable Nvidia to develop new ASL-related products down the road — for example, to improve sign recognition in video-conferencing software or gesture control in cars.

Nvidia also plans to make its database publicly available to developers, potentially leading to advancements such as improved sign recognition in video conferencing or gesture control in vehicles.

By harnessing the pattern-recognition capabilities of AI deep learning trained on noninvasive brain imaging data, the UC San Diego researchers have a proof-of-concept that may one day lead to ...

On Thursday, Nvidia launched a language learning platform called "Signs" using artificial intelligence for American Sign Language learners.