Deep learning-based prediction of structural parameters in FDTD-simulated plasmonic nanostructures
The research creates a new approach to estimate essential dimensions of plasmonic nanoparticles that use the Finite-Difference Time-Domain (FDTD) simulation program. The research team uses EfficientNetB0 alongside ResNet50 and VGG16 deep learning models to obtain quick and exact simulations paramet...
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| Hlavní autoři: | , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Lublin University of Technology
2025-12-01
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| Edice: | Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska |
| Témata: | |
| On-line přístup: | https://ph.pollub.pl/index.php/iapgos/article/view/7300 |
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