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Domain Distribution Alignment for Boosting Multi-Modal ...
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由 Z Wang 著作2023 — This paper proposes a domain distribution alignment method for boosting multi-modal remote sensing image matching. It combines instance comparison and batch ...
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Domain Distribution Alignment for Boosting Multi-Modal ...
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2024年8月23日 — In this paper, the SAR and optical images are set as the sensed and reference images. The effects of different image sizes, training label types ...
domain distribution alignment for boosting multi-modal remote ...
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DOMAIN DISTRIBUTION ALIGNMENT FOR BOOSTING MULTI-MODAL REMOTE SENSING IMAGE MATCHING ; Session: MOP.P1: Feature Extraction and Image Matching with Radar and ...
Chonghua Lv - Google 学术搜索
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Domain Distribution Alignment for Boosting Multi-Modal Remote Sensing Image Matching. Z Wang, D Quan, C Lv, Y Guo, S Wang, Y Gu, L Jiao. IGARSS 2023-2023 IEEE ...
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Readers: Everyone. Domain Distribution Alignment for Boosting Multi-Modal Remote Sensing Image Matching ... Multi-Modal Remote Sensing Image Patch Matching ...
Refining multi-modal remote sensing image matching with ...
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由 Y Liao 著作2024 — This paper aims to elevate matching accuracy by implementing a detailed texture removal strategy that effectively isolates repeatable structural features.
Chonghua Lv
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Domain Distribution Alignment for Boosting Multi-Modal Remote Sensing Image Matching · Zhe WangDou Quan +4 authors. Licheng Jiao. Computer Science ...
Yu Gu's research works | Xidian University and other places
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This paper proposes a novel coarse-to-fine deep learning image registration framework for multi-modal remote sensing images based on two task-specific deep ...
Spatial-Topological-Semantic alignment for cross domain ...
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由 B Li 著作2024 — Domain adaptation is crucial for information integration of remote sensing systems, such as satellite constellations and space stations, to intelligently ...
Multimodal Remote Sensing Image Registration Methods ...
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由 X Zhang 著作2021被引用 53 次 — This paper introduces three theoretical frameworks: namely, area-based, feature-based and deep learning-based methods.