Figure | Working principle and results of the photonic feature extractor. (IMAGE)
Caption
a, The photonic feature extractor imitates a convolutional neural network. The input RF signals (echoes reflected from the targets) from antennas are processed in the analog domain and the output is the extracted features. Features are recorded by analog-to-digital converters (ADCs) and a fully-connected network classifies the targets. b, The photographs of the photonic chip and packaged module. c, The visualization analysis of the experimental results. Before photonic feature extraction, the embedding of targets cannot be easily distinguished. After the photonic feature extraction, the embeddings of the targets are distinguishable.
Credit
by Shaofu Xu, Binshuo Liu, Sicheng Yi, Jing Wang, and Weiwen Zou
Usage Restrictions
Credit must be given to the creator.
License
CC BY