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  "author": "Qiufeng Wang",
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  "author": "Qiufeng Wang",
            
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  "doi": "10.57702/xqs61xne",
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  "doi": "10.57702/xqs61xne",
            
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  "doi_date_published": "2024-12-16",
            
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Xu Yang",
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      "extra_author": "Xu Yang",
            
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      "orcid": ""
            
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    },
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    {
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    {
            
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      "extra_author": "Shuxia Lin",
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      "extra_author": "Shuxia Lin",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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    {
            
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      "extra_author": "Jing Wang",
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      "extra_author": "Jing Wang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Xin Geng",
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      "extra_author": "Xin Geng",
            
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      "orcid": ""
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      "name": "image-classification",
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      "name": "image-classification",
            
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      "title": "Image Classification"
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      "title": "Image Classification"
            
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  "name": "cifar100--imagenet100--and-imagenet",
            
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  "notes": "The dataset used in the paper is CIFAR100, ImageNet100, 
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  "notes": "The dataset used in the paper is CIFAR100, ImageNet100, 
            
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and ImageNet. CIFAR100 consists of 100 object classes and 60,000 
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and ImageNet. CIFAR100 consists of 100 object classes and 60,000 
            
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images. ImageNet100 has 100 object classes and 60,000 color images of 
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images. ImageNet100 has 100 object classes and 60,000 color images of 
            
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size 84\u00d784. ImageNet is a 1,000-class dataset from ILSVRC2012, 
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size 84\u00d784. ImageNet is a 1,000-class dataset from ILSVRC2012, 
            
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providing 1.2 million images for training and 50,000 images for 
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providing 1.2 million images for training and 50,000 images for 
            
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validation.",
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validation.",
            
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  "title": "CIFAR100, ImageNet100, and ImageNet",
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  "title": "CIFAR100, ImageNet100, and ImageNet",
            
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}