This release updates the release that posted earlier on 1/27/26 to clarify the SOURCE of the release. SAN RAMON, CA / ACCESS ...
Modern neuroscience and the computational modeling of the activities of vast, integrated neural networks provide fruitful accounts of how our minds work and learn.
For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...
Abstract: In unmanned aerial vehicle (UAV) ad hoc networks, dynamic wireless channel fluctuations and malicious electromagnetic jamming may severely compromise link reliability, causing rate ...
Background While the incidence of hospital adverse events appeared to be declining before 2019, the COVID-19 pandemic may ...
Abstract: Security vulnerabilities have become increasingly critical with the growing connection of Internet of Things (IoT) devices and industrial control systems to 4G/5G private networks (PNs).
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
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