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English(EN) SCTD 3.0: Sonar Common Target Detection in the Wild - A Large-Scale, Multi-Scene Dataset from Real Marine Surveys

新数据集SCTD 3.0旨在推进水下目标检测

研究人员推出了SCTD 3.0,这是一个旨在利用合成孔径声呐(SAS)改进水下目标检测的大规模数据集。该数据集包含来自自然水域中多频系统捕获的、跨越十个目标类别的超过10,000个真实SAS图像片段。SCTD 3.0包含严格的标注协议,用于细粒度的目标特征描述,并建立了一个多任务基准,以评估深度学习模型在各种条件下的泛化能力。 AI

影响 旨在通过提供一个强大的数据集来训练和评估深度学习模型,从而改进水下目标感知。

排序理由 该集群描述了一个特定计算机视觉任务的新数据集和基准,发表在一篇学术论文中。[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 →

新数据集SCTD 3.0旨在推进水下目标检测

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该集群描述了一个特定计算机视觉任务的新数据集和基准,发表在一篇学术论文中。[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) · Peng Zhang ·

    SCTD 3.0:野外声呐通用目标检测——来自真实海洋调查的大规模、多场景数据集

    arXiv:2608.08106v1 Announce Type: new Abstract: Synthetic Aperture Sonar (SAS) is core for wide-area detection of small underwater targets. However, large-scale, high-quality SAS datasets are scarce, hindering data-driven recognition. Existing benchmarks are small and limited to …