Photonics Research, Volume. 9, Issue 4, B104(2021)
Real-time deep learning design tool for far-field radiation profile
Fig. 1. Illustration of our approach and the loss curve of the neural network. (a) Sketch of a scatterer and its far-field pattern. (b) Loss curve of our neural network.
Fig. 2. Examples of results from our method on: (a) random structures from the test set; and (b) typical shapes with different sizes, compared to the ground truth.
Fig. 3. Two examples of calculating a far-field pattern using our web tool. (a), (b) Two steps of drawing the final structure, which is the one on the right side in Fig.
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Jinran Qie, Erfan Khoram, Dianjing Liu, Ming Zhou, Li Gao. Real-time deep learning design tool for far-field radiation profile[J]. Photonics Research, 2021, 9(4): B104
Special Issue: DEEP LEARNING IN PHOTONICS
Received: Oct. 27, 2020
Accepted: Feb. 2, 2021
Published Online: Apr. 6, 2021
The Author Email: Li Gao (iamlgao@njupt.edu.cn)