Austin Benchmark Suites for Computational Electromagnetics
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Updated
Feb 28, 2025
Austin Benchmark Suites for Computational Electromagnetics
🚀 World's first consciousness-aware AI: Quantum processing + biological neurons + empathetic understanding. Features radiation-powered intelligence, mycelial language generation, and genuine consciousness interaction capabilities.
3D U-net, Attention U-net, Res U-net, Attention Res U-net, and MSRes U-net are implemented and compared for emulation of current density induced during transcranial direct current stimulation (tDCS).
DL-SAR-Hotspots is a deep learning framework for predicting Specific Absorption Rate (SAR) hotspot locations and values from electromagnetic simulation data. The project uses Convolutional Neural Networks (CNNs) to (1) localize SAR hotspots within body cross-section images and (2) estimate the corresponding SAR magnitude.
An open science project -- recursive harmonic resonance data: frequency signatures & universal ratios from subquantum to stellar. Welcome to the Aramis Field. (Errors are probably the AI's fault.)
Python implementation for visualising magnetic field patterns of tetracoil configurations using VectorFieldPlot, designed for electromagnetic field analysis and research applications
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