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15,500 Seconds: Lean UAV Classification Leveraging PEFT and Pre-Trained Networks

15,500 Seconds: Lean UAV Classification Leveraging PEFT and Pre-Trained Networks

来源:Arxiv_logoArxiv
英文摘要

Unmanned Aerial Vehicles (UAVs) pose an escalating security concerns as the market for consumer and military UAVs grows. This paper address the critical data scarcity challenges in deep UAV audio classification. We build upon our previous work expanding novel approaches such as: parameter efficient fine-tuning, data augmentation, and pre-trained networks. We achieve performance upwards of 95\% validation accuracy with EfficientNet-B0.

Andrew P. Berg、Qian Zhang、Mia Y. Wang

军事技术

Andrew P. Berg,Qian Zhang,Mia Y. Wang.15,500 Seconds: Lean UAV Classification Leveraging PEFT and Pre-Trained Networks[EB/OL].(2025-07-02)[2025-07-16].https://arxiv.org/abs/2506.11049.点此复制

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