English(EN) GeoCrossBench: Cross-Band Generalization for Remote Sensing

新基准GeoCrossBench旨在实现遥感模型的跨波段泛化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员推出了GeoCrossBench，这是GeoBench基准的扩展，用于评估遥感基础模型的跨波段泛化能力。这个新基准包括用于标准分布内性能、对未见波段的泛化以及对具有训练波段超集的测试输入的泛化的协议。为了支持这一点，开发了一个名为$\chi$ViT的自监督模型作为基线。使用11,900个NVIDIA H100 GPU小时进行的实验显示，尽管DOFA和Vision Transformer Base等模型在特定设置下表现良好，但在评估未见波段时，所有模型的性能都会显著下降，这凸显了未来遥感模型对更鲁棒的跨波段泛化的需求。 AI

影响该基准和模型开发可能带来更鲁棒的遥感AI，使其能够在不进行昂贵重新训练的情况下适应新的卫星数据。

排序理由该集群描述了一个用于遥感研究的新基准和支持模型，发布在arXiv上。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Hakob Tamazyan, Ani Vanyan, Alvard Barseghyan, Anna Khosrovyan, Evan Shelhamer, Hrant Khachatrian · 2026-09-16 04:00

GeoCrossBench：遥感跨波段泛化

arXiv:2511.02831v2 Announce Type: replace Abstract: The data for remote sensing is constantly acquired, and new data comes from a growing number and diversity of satellites, while the vast majority of labeled data comes from older satellites. As remote-sensing foundation models f…

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GeoCrossBench：遥感跨波段泛化

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