English(EN) YolovN-CBi: A Lightweight and Efficient Architecture for Real-Time Detection of Small UAVs

新的 YolovN-CBi 架构增强了小型无人机的实时检测能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-21 04:00

研究人员开发了一种名为 YolovN-CBi 的新型轻量级架构，专为实时检测小型无人机 (UAV) 而设计。该架构集成了卷积块注意力模块 (CBAM) 和双向特征金字塔网络 (BiFPN)，以增强对小型目标的检测能力。在基准数据集和自定义本地数据集上的评估表明，Yolov5-CBi 变体在小型目标检测的速度-准确性权衡方面优于 YOLOv8 和 YOLOv12 等较新的 YOLO 版本。此外，使用知识蒸馏创建的 CBi 架构的蒸馏版本在准确性和速度方面取得了显著改进，使其适用于边缘部署。 AI

影响这项研究可能带来更高效、更准确的实时无人机检测系统，用于安全和民用领域。

排序理由该项目是一篇学术论文，详细介绍了一种新的计算机视觉模型架构及其评估。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Ami Pandat, Punna Rajasekhar, Gopika Vinod, Rohit Shukla · 2026-08-21 04:00

YolovN-CBi：一种用于小型无人机实时检测的轻量级高效架构

arXiv:2512.18046v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles, commonly known as, drones pose increasing risks in civilian and defense settings, demanding accurate and real-time drone detection systems. However, detecting drones is challenging because of their smal…

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YolovN-CBi：一种用于小型无人机实时检测的轻量级高效架构

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