{
  "id": 295799,
  "title": "ZeroCostDL4Mic | 38 Notebooks for Common Deep Learning Approaches for Microscopy Imaging.",
  "url": "/competitions/sartorius-cell-instance-segmentation/discussion/295799",
  "author_name": "Faisal Alsrheed",
  "post_date": "2021-12-17T22:29:39.264000",
  "votes": 5,
  "comment_count": 0,
  "views": 0,
  "content": "<h4>What is ZeroCostDL4Mic?</h4>\n<pre><code>ZeroCostDL4Mic is a toolbox for the training and implementation of common Deep Learning approaches to microscopy imaging. It exploits the ease-of-use and access to GPU provided by Google Colab.\n\nZeroCostDL4Mic provides fully annotated Google Colab optimised Jupyter Notebooks for popular pre-existing networks. These cover a range of important image analysis tasks (e.g. segmentation, denoising, restoration, label-free prediction)\n</code></pre>\n<p><img src=\"https://i.postimg.cc/MTqk7VyJ/Main-Fig1-Wiki-v11.png\" alt=\"\"></p>\n<hr>\n<h5>See the full list of the Notebooks here:</h5>\n<p><a href=\"https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki\" target=\"_blank\">https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki</a></p>\n<p><img src=\"https://i.postimg.cc/d1b5RYMk/0C1.jpg\" alt=\"\"></p>\n<p><img src=\"https://i.postimg.cc/R0NrX4YX/0C2.jpg\" alt=\"\"></p>\n<hr>\n<h4>Conference talk about  ZeroCostDL4Mic</h4>\n<p><img src=\"https://i.postimg.cc/44MY5xFF/0Cyou.jpg\" alt=\"\"><br>\n<img src=\"https://i.postimg.cc/g0vy961J/0Cyou2.jpg\" alt=\"\"></p>\n<p><a href=\"https://youtu.be/rCEbYOnNJp0\" target=\"_blank\">https://youtu.be/rCEbYOnNJp0</a></p>",
  "messages": [
    {
      "id": 1621642,
      "postDate": "2021-12-17T22:29:39.263Z",
      "content": "<h4>What is ZeroCostDL4Mic?</h4>\n<pre><code>ZeroCostDL4Mic is a toolbox for the training and implementation of common Deep Learning approaches to microscopy imaging. It exploits the ease-of-use and access to GPU provided by Google Colab.\n\nZeroCostDL4Mic provides fully annotated Google Colab optimised Jupyter Notebooks for popular pre-existing networks. These cover a range of important image analysis tasks (e.g. segmentation, denoising, restoration, label-free prediction)\n</code></pre>\n<p><img src=\"https://i.postimg.cc/MTqk7VyJ/Main-Fig1-Wiki-v11.png\" alt=\"\"></p>\n<hr>\n<h5>See the full list of the Notebooks here:</h5>\n<p><a href=\"https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki\" target=\"_blank\">https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki</a></p>\n<p><img src=\"https://i.postimg.cc/d1b5RYMk/0C1.jpg\" alt=\"\"></p>\n<p><img src=\"https://i.postimg.cc/R0NrX4YX/0C2.jpg\" alt=\"\"></p>\n<hr>\n<h4>Conference talk about  ZeroCostDL4Mic</h4>\n<p><img src=\"https://i.postimg.cc/44MY5xFF/0Cyou.jpg\" alt=\"\"><br>\n<img src=\"https://i.postimg.cc/g0vy961J/0Cyou2.jpg\" alt=\"\"></p>\n<p><a href=\"https://youtu.be/rCEbYOnNJp0\" target=\"_blank\">https://youtu.be/rCEbYOnNJp0</a></p>",
      "rawMarkdown": "#### What is ZeroCostDL4Mic?\n\n```\nZeroCostDL4Mic is a toolbox for the training and implementation of common Deep Learning approaches to microscopy imaging. It exploits the ease-of-use and access to GPU provided by Google Colab.\n\nZeroCostDL4Mic provides fully annotated Google Colab optimised Jupyter Notebooks for popular pre-existing networks. These cover a range of important image analysis tasks (e.g. segmentation, denoising, restoration, label-free prediction)\n```\n \n![](https://i.postimg.cc/MTqk7VyJ/Main-Fig1-Wiki-v11.png)\n\n____________________________________\n\n##### See the full list of the Notebooks here:\nhttps://github.com/HenriquesLab/ZeroCostDL4Mic/wiki\n\n![](https://i.postimg.cc/d1b5RYMk/0C1.jpg)\n\n![](https://i.postimg.cc/R0NrX4YX/0C2.jpg)\n\n\n\n____________________________________\n\n#### Conference talk about  ZeroCostDL4Mic\n![](https://i.postimg.cc/44MY5xFF/0Cyou.jpg)\n![](https://i.postimg.cc/g0vy961J/0Cyou2.jpg)\n\nhttps://youtu.be/rCEbYOnNJp0\n\n\n\n\n",
      "votes": 5
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "1621642": "#### What is ZeroCostDL4Mic?\n\n```\nZeroCostDL4Mic is a toolbox for the training and implementation of common Deep Learning approaches to microscopy imaging. It exploits the ease-of-use and access to GPU provided by Google Colab.\n\nZeroCostDL4Mic provides fully annotated Google Colab optimised Jupyter Notebooks for popular pre-existing networks. These cover a range of important image analysis tasks (e.g. segmentation, denoising, restoration, label-free prediction)\n```\n \n![](https://i.postimg.cc/MTqk7VyJ/Main-Fig1-Wiki-v11.png)\n\n____________________________________\n\n##### See the full list of the Notebooks here:\nhttps://github.com/HenriquesLab/ZeroCostDL4Mic/wiki\n\n![](https://i.postimg.cc/d1b5RYMk/0C1.jpg)\n\n![](https://i.postimg.cc/R0NrX4YX/0C2.jpg)\n\n\n\n____________________________________\n\n#### Conference talk about  ZeroCostDL4Mic\n![](https://i.postimg.cc/44MY5xFF/0Cyou.jpg)\n![](https://i.postimg.cc/g0vy961J/0Cyou2.jpg)\n\nhttps://youtu.be/rCEbYOnNJp0\n\n\n\n\n"
  }
}