English(EN) YOLO12-MambaScan: An Efficient Object Detector with High-Frequency Enhancement and State-Space Modeling

YOLO12-MambaScan 利用状态空间建模增强了航空影像目标检测能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-15 04:00

研究人员开发了YOLO12-MambaScan，这是一种专为航空影像设计的新型目标检测模型。该模型通过引入新颖的高频增强卷积模块和基于Mamba的全局上下文模块来增强YOLO12架构。这些新增功能旨在通过保留关键的边缘、角点和纹理信息来改善对杂乱场景中小目标的检测。在VisDrone数据集上的测试中，YOLO12-MambaScan达到了60.0%的mAP@50，展示了航空影像目标检测任务在准确性和效率之间的良好平衡。 AI

影响该模型提高了航空影像中小目标的检测能力，可能有助于资源监测和交通管理等应用。

排序理由这是一篇详细介绍新模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Hao Wang · 2026-09-15 04:00

YOLO12-MambaScan：一种高效的具有高频增强和状态空间建模的目标检测器

arXiv:2609.13647v1 Announce Type: new Abstract: The rapid development of unmanned aerial vehicle (UAV) technology has made aerial-image object detection increasingly important for natural-resource monitoring, traffic management, and disaster response. Detecting small objects in a…

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YOLO12-MambaScan：一种高效的具有高频增强和状态空间建模的目标检测器

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