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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| Egile Nagusiak: | , , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
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MDPI AG
2024-08-01
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| Saila: | Remote Sensing |
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| Sarrera elektronikoa: | https://www.mdpi.com/2072-4292/16/16/3109 |
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