Classification of Metal Handwritten Digits Based on Microwave Diffractive Deep Neural Network

Recently, optical diffractive deep neural networks (D2NNs) have shown unprecedented superiority in terms of processing speed and power consumption. However, in the microwave band, complicated classification based on D2NN needs further investigation, which may accelerate the artificial intelligent ta...

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Veröffentlicht in:	Advanced optical materials 2024-03, Vol.12 (7), p.n/a
Hauptverfasser:	Gu, Ze, Ma, Qian, Gao, Xinxin, You, Jian Wei, Cui, Tie Jun
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial neural networks Classification Computer simulation diffractive neural networks Electromagnetic radiation Engraving Handwriting metasurfaces Microwave frequencies Neural networks optical neural networks Phase distribution Power consumption
Online-Zugang:	Volltext
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