Abstract: Convolutional neural network (CNN) is greatly affected by many factors, such as the gradient loss, the adequacy of feature extraction and the number of channels and multi-sensor traffic ...
National Grid has introduced Triton, a new digital twin and data visualization tool designed to support electricity network planning. The tool was developed in collaboration with Atos and is intended ...
Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...
The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...
This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...
ABSTRACT: We present a novel integrated mathematical and numerical framework for the nonlinear Schrödinger equation in open quantum systems under electromagnetic fields, with a particular focus on ...
A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
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