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Innovation - Computer Science - 03.04.2023
Eye-tracking research is a peek into the future of mobile device interaction
A new study exploring how mobile devices can be controlled solely by the movements of users' eyes could offers a peek into the future of gaze-based interactions with smartphones, researchers say. Human-computer interaction specialists from universities in Scotland, Germany and Portugal have taken a closer look at how eyes can be used to control mobile devices and made a series of recommendations on how to integrate gaze-interaction into future generations of tech.

Computer Science - Environment - 07.03.2023
Phone-based measurements provide fast, accurate information about the health of forests
Phone-based measurements provide fast, accurate information about the health of forests
Researchers have developed an algorithm that uses computer vision techniques to accurately measure trees almost five times faster than traditional, manual methods. Ground-based measurements are hugely valuable, but also time-consuming. We wanted to know whether we could automate this process. Amelia Holcomb The researchers, from the University of Cambridge, developed the algorithm, which gives an accurate measurement of tree diameter, an important measurement used by scientists to monitor forest health and levels of carbon sequestration.

Health - Computer Science - 09.02.2023
Test that can identify respiratory viruses within five minutes
Scientists have developed a world-first diagnostic test, powered by artificial intelligence, that can identify known respiratory viruses within five minutes from just one nasal or throat swab. The new diagnostic test could replace current methods that are limited to testing for only one infection, such as a lateral flow test for COVID-19, or otherwise are either lab-based and time-consuming or fast and less accurate.

Environment - Computer Science - 09.01.2023
AI to monitor changes to globally important glacier
AI to monitor changes to globally important glacier
Scientists have developed AI to track the development of crevasses - or fractures - on the Thwaites Glacier ice tongue in west Antarctica. Crevasses are indicators of stress building-up in the glacier. A team of researchers from the University of Leeds and University of Bristol have adapted an AI algorithm originally developed to identify cells in microscope images to spot crevasses forming in the ice from satellite images.