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AOHDL: Adversarial Optimized Hybrid Deep Learning Design for Preventing Attack in Radar Target Detection

In autonomous driving, Frequency-Modulated Continuous-Wave (FMCW) radar has gained widespread acceptance for target detection due to its resilience and dependability under diverse weather and illumination circumstances. Although deep learning radar target identification models have seen fast improve...

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Principais autores: Muhammad Moin Akhtar, Yong Li, Wei Cheng, Limeng Dong, Yumei Tan, Langhuan Geng
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-08-01
Serier:Remote Sensing
Fag:
RTD
adversarial examples
generative adversarial network (GAN)
deep learning
FMCW
Online adgang:https://www.mdpi.com/2072-4292/16/16/3109
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