AI systems now operate on a very large scale. Modern deep learning models contain billions of parameters and are trained on large datasets. Therefore, they produce strong accuracy. However, their ...
Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
Sean Turner, a DOE senior engineer, is using AI at Oak Ridge National Laboratory to improve water resource management for ...
Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
An important but unresolved question in deep learning for EEG decoding is which features neural networks learn to solve the task. Prior interpretability studies have mainly explained individual ...
Max Delbrück Center for Molecular Medicine in the Helmholtz Association Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment.
Abstract: This article presents a physics-informed deep learning framework using deep neural networks (DNNs) for metasurface (MS) design. By integrating equivalent circuit parameters as physically ...
This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...
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