GeoMamba with Geometric Feature Injection and Geometric Consistency Constraint modules achieves 63.3% mAP and 77.0% Rank-1 on the new FGOS-as dataset for unaligned optical-SAR fine-grained retrieval.
Learning source-invariant deep hashing convolutional neural networks for cross-source remote sensing image retrieval,
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GeoMamba: A Geometry-driven MambaVision Framework and Dataset for Fine-grained Optical-SAR Object Retrieval
GeoMamba with Geometric Feature Injection and Geometric Consistency Constraint modules achieves 63.3% mAP and 77.0% Rank-1 on the new FGOS-as dataset for unaligned optical-SAR fine-grained retrieval.