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  "fetched_at": "2026-10-19T07:35:22Z",
  "source_url": "https://www.kaggle.com/competitions/deep-learning-competition-cs-2020/data",
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    {
      "name": "rules",
      "content": "    \n\t\n    <h3>One account per team participant</h3>\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n    <h3>No private sharing outside teams</h3>\n    <p>\n        Privately sharing code or data outside of teams is not permitted.\n    </p>\n   <h3> It is **NOT ALLOWED** to use Keras.Applications </h3>\n    <h3>Submission Limits</h3>\n    <p>You may submit a maximum of 3 entries per day.</p>\n    <p>You may select up to 2 final submissions for judging.</p>\n    <h3>Competition Timeline</h3>\n    <p>Start Date: <strong>10/4/2020</strong></p>\n    <p>End Date: <strong> One day before the practical exam </strong></p>\n\t",
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      "name": "data-description",
      "content": "<h1> Dataset description </h1>\n<p>\nThe dataset is organized into 2 folders (train and test) and contains subfolders for the train category (COVID-19 and Pneumonia/Normal). There are 5,266 X-Ray training images, 1,341 Normal X-Ray and 3,925 (COVID-19 and Pneumonia) images.\n\n<h2>Files description</h2>\n<ul>\n<li><strong>train.rar</strong> - the training set</li>\n<li><strong>test.rar</strong> - the test set</li>\n<li><strong>Submit.csv</strong> - a sample submission file in the correct format</li>\n<li><strong>Names.csv</strong> this file contains the IDs of the two classes</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>Image</strong> - the name of the X-Ray image </li>\n<li><strong>Label</strong> - the predicted class for that ID</li>\n</ul>",
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    {
      "name": "Description",
      "content": "<h1> Introduction </h1>\nWelcome to the competition. This competition is for CS Students in Neural Network and Deep Learning course at FCIS. The goal of the competition is to build deep learning models that can diagnose COVID-19 and Pneumonia cases using chest X-Ray Images. Let's help the community with useful things!\n\n<h1> Medical Background </h1>\n<p>\nCOVID-19 and Pneumonia present several unique features. While the diagnosis of COVID-19 is confirmed using polymerase chain reaction (PCR), infected patients with pneumonia may present on chest X-ray and computed tomography (CT) images with a pattern that is only moderately characteristic for the human eye. COVID-19’s rate of transmission depends on our capacity to reliably identify infected patients with a low rate of false negatives. In addition, a low rate of false positives is required to avoid further increasing the burden on the healthcare system by unnecessarily exposing patients to quarantine if that is not required. Along with proper infection control, it is evident that timely detection of the disease would enable the implementation of all the supportive care required by patients affected by COVID-19 and Pneumonia.\n</p>\n\n",
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    {
      "name": "Evaluation",
      "content": "<p>You have to submit a file in CSV format named as 'submit.csv'.</p>\n<hr>\n<p>The evaluation metric for this competition is the overall accuracy </p><p> \n\n</p><h2>Submission Format</h2>\n<p><strong> The file contains 2 column, the first column is ID, which is the name of the test image. The second column is label, which is your predicted label for the image </strong> </p>\n<p>The file should contain a header and have the following format:</p>\n<pre>id,label<br>00070.jpg,1<br></pre>",
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