Abstract: Mobile edge computing (MEC) is emerging as a critical paradigm to meet the growing computational demands of wireless devices. However, edge servers, wireless devices, and service types in ...
Background Patients with severe aortic stenosis (AS) are at high risk of mortality, regardless of symptom status. Despite ...
The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
More than 800 U.S. TikTok users shared their data with The Washington Post. We used it to find out why some people become power users, spending hours per day scrolling. Each circle in the chart ...
A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...
Abstract: The success of deep learning (DL) is often achieved at the expense of large model sizes and high computational complexity during both training and post-training inferences, making it ...
Background: Early diagnosis can significantly improve survival rate of Pancreatic ductal adenocarcinoma (PDAC), but due to the insidious and non-specific early symptoms, most patients are not suitable ...
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