{
  "citation": "@inproceedings{wei2022learning,\n  title={Learning with Noisy Labels Revisited: A Study Using Real-World Human \n  Annotations},\n  author={Jiaheng Wei and Zhaowei Zhu and Hao Cheng and Tongliang Liu and Gang \n  Niu and Yang Liu},\n  booktitle={International Conference on Learning Representations},\n  year={2022},\n  url={https://openreview.net/forum?id=TBWA6PLJZQm}\n}",
  "description": "A re-labeled version of CIFAR-100 with real human annotation errors. For every \npair (image, label) in the original CIFAR-100 train set, it provides an \nadditional label given by a real human annotator.",
  "downloadSize": "168513733",
  "fileFormat": "tfrecord",
  "location": {
    "urls": [
      "https://www.cs.toronto.edu/~kriz/cifar.html"
    ]
  },
  "moduleName": "tensorflow_datasets.image_classification.cifar100_n.cifar100_n",
  "name": "cifar100_n",
  "releaseNotes": {
    "1.0.0": "Initial release.",
    "1.0.1": "Fixed correspondence between annotations and images."
  },
  "splits": [
    {
      "filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
      "name": "train",
      "numBytes": "118721317",
      "shardLengths": [
        "50000"
      ]
    },
    {
      "filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
      "name": "test",
      "numBytes": "23961198",
      "shardLengths": [
        "10000"
      ]
    }
  ],
  "version": "1.0.1"
}