{
  "fetched_at": "2026-10-20T07:22:32Z",
  "source_url": "https://www.kaggle.com/competitions/b3-data-information-coursetutorial/data",
  "pages": [
    {
      "name": "data-description",
      "content": "引用元\nhttps://www.kaggle.com/jessicali9530/stanford-dogs-dataset\n\n\n\n\nContext\nThe Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization. It was originally collected for fine-grain image categorization, a challenging problem as certain dog breeds have near identical features or differ in colour and age.\n\nContent\nNumber of categories: 120\nNumber of images: 20,580\nAnnotations: Class labels, Bounding boxes\nAcknowledgements\nThe original data source is found on http://vision.stanford.edu/aditya86/ImageNetDogs/ and contains additional information on the train/test splits and baseline results.\n\nIf you use this dataset in a publication, please cite the dataset on the following papers:\n\nAditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao and Li Fei-Fei. Novel dataset for Fine-Grained Image Categorization. First Workshop on Fine-Grained Visual Categorization (FGVC), IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [pdf] [poster] [BibTex]\n\nSecondary:\nJ. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, ImageNet: A Large-Scale Hierarchical Image Database. IEEE Computer Vision and Pattern Recognition (CVPR), 2009. [pdf] [BibTex]\n\nBanner Image from Hannah Lim on Unsplash",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "データ情報学　InClassコンペティション　チュートリアル\n概要\n犬種を特定する多クラス分類タスクです。\n\n第３回目の授業終了まで",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "# 評価指標\n評価はROC AUCスコアで行います。\nhttps://note.nkmk.me/python-sklearn-roc-curve-auc-score/\nを参考にしてください。\n\n# 提出形式\n提出形式は、sample_submission.csvを書き換えたものを提出してください。\n以下の形式になるようプログラムが提供されています。\n\nImage,Label\nn02113712_430.jpg,0",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": "# 写真を見てラベルを選択しないでください",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
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}