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English(EN) UAV Thermal Imagery for Inert Ordnance Screening: Multi Campaign Dataset Development,Object Detection, and Practical Recommendations

无人机热成像数据集和模型助力未爆弹药筛查

研究人员开发了一个新的数据集和目标检测模型,用于使用无人机热成像筛查未爆弹药(UXO)。该数据集在各种环境条件下进行了四次野外活动收集,包含超过 5,800 对标记的热图像。对 YOLOV11lRT-DETR-R50 等目标检测算法进行了训练和评估,以创建自动候选目标检测模型。该研究为人道主义排雷行动提供了实践建议,强调了同时收集热成像和 RGB 图像的重要性,使用具有代表性的本地数据进行模型校准,并保留人工审查以进行最终评估。 AI

影响 这项研究可以通过自动检测未爆弹药来提高排雷作业的效率和安全性。

排序理由 该集群包含一篇学术论文,详细介绍了用于目标检测的新数据集和方法论。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

无人机热成像数据集和模型助力未爆弹药筛查

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该集群包含一篇学术论文,详细介绍了用于目标检测的新数据集和方法论。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Chad Melton, PhD., Annabelle Kelton ·

    无人机热成像用于惰性弹药筛查:多战役数据集开发、目标检测及实践建议

    arXiv:2609.01738v1 Announce Type: new Abstract: Unexploded ordnance (UXO) continues to restrict civilian access, agricultural activity, infrastructure recovery, and environmental remediation in contaminated areas around the world. This study created a multi campaign UAV thermal i…