February 7, 2020 Dataset Open Access

Anonymous

JSON Export

{
  "files": [
    {
      "links": {
        "self": "https://zenodo.org/api/files/d3287b3e-144f-41e4-a60d-965185cf6811/LICENSE.md"
      }, 
      "checksum": "md5:54a45176ac56e3aea7f286d3e1d10538", 
      "bucket": "d3287b3e-144f-41e4-a60d-965185cf6811", 
      "key": "LICENSE.md", 
      "type": "md", 
      "size": 14196
    }, 
    {
      "links": {
        "self": "https://zenodo.org/api/files/d3287b3e-144f-41e4-a60d-965185cf6811/SlimageNet64.tar.bz2"
      }, 
      "checksum": "md5:9a65cef93aa81029b5ce70094ed8978a", 
      "bucket": "d3287b3e-144f-41e4-a60d-965185cf6811", 
      "key": "SlimageNet64.tar.bz2", 
      "type": "bz2", 
      "size": 1654468852
    }
  ], 
  "owners": [
    91493
  ], 
  "doi": "10.5281/zenodo.3672132", 
  "stats": {
    "version_unique_downloads": 178.0, 
    "unique_views": 633.0, 
    "views": 697.0, 
    "version_views": 698.0, 
    "unique_downloads": 178.0, 
    "version_unique_views": 634.0, 
    "volume": 916584446110.0, 
    "version_downloads": 582.0, 
    "downloads": 582.0, 
    "version_volume": 916584446110.0
  }, 
  "links": {
    "doi": "https://doi.org/10.5281/zenodo.3672132", 
    "conceptdoi": "https://doi.org/10.5281/zenodo.3672131", 
    "bucket": "https://zenodo.org/api/files/d3287b3e-144f-41e4-a60d-965185cf6811", 
    "conceptbadge": "https://zenodo.org/badge/doi/10.5281/zenodo.3672131.svg", 
    "html": "https://zenodo.org/record/3672132", 
    "latest_html": "https://zenodo.org/record/3672132", 
    "badge": "https://zenodo.org/badge/doi/10.5281/zenodo.3672132.svg", 
    "latest": "https://zenodo.org/api/records/3672132"
  }, 
  "conceptdoi": "10.5281/zenodo.3672131", 
  "created": "2020-02-19T20:09:41.791742+00:00", 
  "updated": "2020-02-24T10:10:17.204645+00:00", 
  "conceptrecid": "3672131", 
  "revision": 5, 
  "id": 3672132, 
  "metadata": {
    "access_right_category": "success", 
    "doi": "10.5281/zenodo.3672132", 
    "description": "<p>SlimageNet64 is new variant of ImageNet64&times;64&nbsp;(Chrabaszcz et al., 2017),&nbsp;derived<br>\nfrom Slim and ImageNet. SlimageNet64 is ideal for few-shot learning, continual learning and meta-learning research. It consists of 200 instances from each of the 1000 object categories of the ILSVRC-2012 dataset (Krizhevsky et al., 2012; Russakovsky et al., 2015), for a total of 200K RGB images with a resolution of 64 &times; 64 &times; 3 pixels. We created this dataset from the downscaled version of ILSVRC-2012, ImageNet64x64, as reported in (Chrabaszcz et al., 2017), using the box downsampling Pillow library.</p>", 
    "license": {
      "id": "other-nc"
    }, 
    "title": "SlimageNet64", 
    "relations": {
      "version": [
        {
          "count": 1, 
          "index": 0, 
          "parent": {
            "pid_type": "recid", 
            "pid_value": "3672131"
          }, 
          "is_last": true, 
          "last_child": {
            "pid_type": "recid", 
            "pid_value": "3672132"
          }
        }
      ]
    }, 
    "keywords": [
      "Few-Shot Learning, Continual Few-Shot Learning, Meta-Learning, Benchmark, Benchmarks, Dataset, Datasets"
    ], 
    "publication_date": "2020-02-07", 
    "creators": [
      {
        "affiliation": "Anonymous", 
        "name": "Anonymous"
      }
    ], 
    "access_right": "open", 
    "resource_type": {
      "type": "dataset", 
      "title": "Dataset"
    }, 
    "related_identifiers": [
      {
        "scheme": "doi", 
        "identifier": "10.5281/zenodo.3672131", 
        "relation": "isVersionOf"
      }
    ]
  }
}