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  "author": "Ce Wang",
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  "author": "Ce Wang",
            
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  "author_email": "",
            
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  "citation": [],
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  "defined_in": "https://doi.org/10.48550/arXiv.2405.07044",
            
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  "doi": "10.57702/qeycvmzy",
            
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  "doi_date_published": "2024-12-16",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Wanjie Sun",
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      "extra_author": "Wanjie Sun",
            
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      "name": "image-super-resolution",
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      "name": "image-super-resolution",
            
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      "title": "Image Super-Resolution"
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      "title": "Image Super-Resolution"
            
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    },
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      "description": "",
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      "description": "",
            
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      "name": "remote-sensing",
            
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      "title": "Remote Sensing"
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      "title": "Remote Sensing"
            
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  "metadata_modified": "2024-12-16T18:38:29.682834",
            
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  "name": "cross-modal-super-resolution-dataset--cmsrd-",
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  "name": "cross-modal-super-resolution-dataset--cmsrd-",
            
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  "notes": "Remote sensing images captured by different platforms 
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  "notes": "Remote sensing images captured by different platforms 
            
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exhibit significant disparities in spatial resolution. Large scale 
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exhibit significant disparities in spatial resolution. Large scale 
            
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factor super-resolution (SR) algorithms are vital for maximizing the 
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factor super-resolution (SR) algorithms are vital for maximizing the 
            
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utilization of low-resolution (LR) satellite data captured from 
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utilization of low-resolution (LR) satellite data captured from 
            
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orbit.",
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orbit.",
            
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  "title": "Cross-Modal Super-Resolution Dataset (CMSRD)",
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}