English(EN) MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detection

MambaDSF框架增强声纳小目标检测能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

研究人员开发了MambaDSF，一个用于检测声纳图像中小目标的新型框架。这种混合方法结合了基于Mamba的骨干网络和扩张特征融合，以有效地捕捉局部和全局声学上下文。该系统引入了新的损失函数来提高小目标的训练稳定性，并在UATD基准测试中表现出色，优于现有探测器。 AI

影响引入了一种新的水下目标检测架构，有望提升自主水下航行器能力。

排序理由这是一篇详细介绍特定领域新技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

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arXiv cs.CV TIER_1 English(EN) · Hui Lin, Jiayi Li, Jing Wang, Shenghui Rong · 2026-05-26 04:00

MambaDSF：用于声纳小目标检测的多尺度SSM与扩张特征融合

arXiv:2605.24928v1 Announce Type: new Abstract: Sonar imaging is the primary modality for underwater target detection, yet small targets remain difficult to detect due to insufficient pixel coverage, low acoustic contrast, and scale ambiguity across imaging ranges. CNN-based dete…