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- W4200025731 abstract "Deep learning-based radar signal recognition is considered one of the important technologies in the field of electronic countermeasure (ECM). However, existing deep learning-based methods require much time to design a specific neural network by experts for recognizing radar signals. It is difficult to employ these methods in real application scenarios. To solve this problem, we proposed an effective radar signal recognition method using neural architecture search (NAS) to automatically design convolutional neural networks (CNN). Experiments are given to validate the proposed method via comparing with both machine learning and deep learning-based methods. Experimental results show that the proposed method can achieve the optimal accuracy with low parameters and floating-point operations." @default.
- W4200025731 created "2021-12-31" @default.
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- W4200025731 date "2021-09-01" @default.
- W4200025731 modified "2023-09-27" @default.
- W4200025731 title "An Effective Radar Signal Recognition Method Using Neural Architecture Search" @default.
- W4200025731 doi "https://doi.org/10.1109/vtc2021-fall52928.2021.9625235" @default.
- W4200025731 hasPublicationYear "2021" @default.
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