Enhancement of Non-Destructive Measurement Resolution with Neural Networks
Ergün Şimşek, Emerson K. Cho · 2024
Similar to image sharpening, the resolution of measured electromagnetic fields can be enhanced with machine learning. We numerically demonstrate that a λ/10 spatial resolution is achievable even with probes that are a few wavelengths wide, while maintaining a maximum relative error of less than 3%.