{
  "id": 159515,
  "title": "List of Important Research Papers for Competition",
  "url": "/competitions/alaska2-image-steganalysis/discussion/159515",
  "author_name": "",
  "post_date": "2020-06-17T17:28:29.646920Z",
  "votes": 39,
  "comment_count": 13,
  "views": 0,
  "content": "<ol>\n<li><a href=\"https://arxiv.org/ftp/arxiv/papers/1704/1704.08378.pdf\">Deep Convolutional Neural Network to Detect J-UNIWARD</a></li>\n<li><a href=\"https://arxiv.org/pdf/1906.00697.pdf\">CNN-based Steganalysis and Parametric Adversarial Embedding: a Game-Theoretic Framework</a></li>\n<li><a href=\"https://arxiv.org/pdf/1906.11525.pdf\">Pooled Steganalysis in JPEG: how to deal with the spreading strategy?</a></li>\n<li><a href=\"https://arxiv.org/pdf/1904.01444.pdf\">Deep Learning in steganography and steganalysis from 2015 to 2018</a></li>\n<li><a href=\"https://arxiv.org/pdf/1711.09335.pdf\">JPEG Steganalysis Based on DenseNet</a></li>\n<li><a href=\"https://arxiv.org/pdf/1611.03233.pdf\">Large-scale JPEG image steganalysis using hybrid deep-learning framework</a></li>\n<li><a href=\"https://arxiv.org/pdf/1605.07946.pdf\">Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key Erratum note</a></li>\n</ol>",
  "messages": [
    {
      "id": "890769",
      "postDate": "06/17/2020 17:28:29",
      "content": "<ol>\n<li><a href=\"https://arxiv.org/ftp/arxiv/papers/1704/1704.08378.pdf\">Deep Convolutional Neural Network to Detect J-UNIWARD</a></li>\n<li><a href=\"https://arxiv.org/pdf/1906.00697.pdf\">CNN-based Steganalysis and Parametric Adversarial Embedding: a Game-Theoretic Framework</a></li>\n<li><a href=\"https://arxiv.org/pdf/1906.11525.pdf\">Pooled Steganalysis in JPEG: how to deal with the spreading strategy?</a></li>\n<li><a href=\"https://arxiv.org/pdf/1904.01444.pdf\">Deep Learning in steganography and steganalysis from 2015 to 2018</a></li>\n<li><a href=\"https://arxiv.org/pdf/1711.09335.pdf\">JPEG Steganalysis Based on DenseNet</a></li>\n<li><a href=\"https://arxiv.org/pdf/1611.03233.pdf\">Large-scale JPEG image steganalysis using hybrid deep-learning framework</a></li>\n<li><a href=\"https://arxiv.org/pdf/1605.07946.pdf\">Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key Erratum note</a></li>\n</ol>",
      "rawMarkdown": "1. [Deep Convolutional Neural Network to Detect J-UNIWARD](https://arxiv.org/ftp/arxiv/papers/1704/1704.08378.pdf)\n2. [CNN-based Steganalysis and Parametric Adversarial Embedding: a Game-Theoretic Framework](https://arxiv.org/pdf/1906.00697.pdf)\n3. [Pooled Steganalysis in JPEG: how to deal with the spreading strategy?](https://arxiv.org/pdf/1906.11525.pdf)\n4. [Deep Learning in steganography and steganalysis from 2015 to 2018](https://arxiv.org/pdf/1904.01444.pdf)\n5. [JPEG Steganalysis Based on DenseNet](https://arxiv.org/pdf/1711.09335.pdf)\n6. [Large-scale JPEG image steganalysis using hybrid deep-learning framework](https://arxiv.org/pdf/1611.03233.pdf)\n7. [Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key Erratum note](https://arxiv.org/pdf/1605.07946.pdf)",
      "votes": null
    },
    {
      "id": "893742",
      "postDate": "06/19/2020 21:05:35",
      "content": "<p>good collection! </p>",
      "rawMarkdown": "good collection!",
      "votes": null
    },
    {
      "id": "894655",
      "postDate": "06/20/2020 16:24:27",
      "content": "<p>Thanks <a href=\"/nandinivineeth\">@nandinivineeth</a> </p>",
      "rawMarkdown": "Thanks @nandinivineeth",
      "votes": null
    },
    {
      "id": "907915",
      "postDate": "06/30/2020 08:45:44",
      "content": "<p>Thanks for the links</p>",
      "rawMarkdown": "Thanks for the links",
      "votes": null
    },
    {
      "id": "908292",
      "postDate": "06/30/2020 13:41:29",
      "content": "<p>You are welcome <a href=\"/ashkhagan\">@ashkhagan</a> </p>",
      "rawMarkdown": "You are welcome @ashkhagan",
      "votes": null
    },
    {
      "id": "909512",
      "postDate": "06/30/2020 16:17:48",
      "content": "<p>Thank you Ishan for sharing!</p>",
      "rawMarkdown": "Thank you Ishan for sharing!",
      "votes": null
    },
    {
      "id": "909666",
      "postDate": "06/30/2020 18:14:59",
      "content": "<p>Welcome <a href=\"/mdselimreza\">@mdselimreza</a> . I hope it helps you.</p>",
      "rawMarkdown": "Welcome @mdselimreza . I hope it helps you.",
      "votes": null
    },
    {
      "id": "909859",
      "postDate": "06/30/2020 21:41:10",
      "content": "<p>Thanks <a href=\"/ishandutta\">@ishandutta</a> for the links, they were helpful!</p>",
      "rawMarkdown": "Thanks @ishandutta for the links, they were helpful!",
      "votes": null
    },
    {
      "id": "910357",
      "postDate": "07/01/2020 05:46:20",
      "content": "<p>Thanks <a href=\"/ishandutta\">@ishandutta</a>  for sharing. Good collection!!!</p>",
      "rawMarkdown": "Thanks @ishandutta  for sharing. Good collection!!!",
      "votes": null
    },
    {
      "id": "910899",
      "postDate": "07/01/2020 12:42:56",
      "content": "<p>Thanks !!</p>",
      "rawMarkdown": "Thanks !!",
      "votes": null
    },
    {
      "id": "910942",
      "postDate": "07/01/2020 13:16:27",
      "content": "<p>Welcome <a href=\"/wusihan\">@wusihan</a> </p>",
      "rawMarkdown": "Welcome @wusihan",
      "votes": null
    },
    {
      "id": "910944",
      "postDate": "07/01/2020 13:17:06",
      "content": "<p>Welcome <a href=\"/shyamrn\">@shyamrn</a> </p>",
      "rawMarkdown": "Welcome @shyamrn",
      "votes": null
    },
    {
      "id": "910947",
      "postDate": "07/01/2020 13:17:29",
      "content": "<p>You are welcome <a href=\"/krishvanapalli\">@krishvanapalli</a> </p>",
      "rawMarkdown": "You are welcome @krishvanapalli",
      "votes": null
    },
    {
      "id": "1235093",
      "postDate": "03/11/2021 20:09:27",
      "content": "<p>Thank you.</p>",
      "rawMarkdown": "Thank you.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1235093,
      "author_name": "mohamedbakrey",
      "author_url": "",
      "post_date": "03/11/2021 20:09:27",
      "content": "<p>Thank you.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 893742,
      "author_name": "nandinivineeth",
      "author_url": "",
      "post_date": "06/19/2020 21:05:35",
      "content": "<p>good collection! </p>",
      "votes": null,
      "replies": [
        {
          "id": 894655,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "06/20/2020 16:24:27",
          "content": "<p>Thanks <a href=\"/nandinivineeth\">@nandinivineeth</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 907915,
      "author_name": "ashkhagan",
      "author_url": "",
      "post_date": "06/30/2020 08:45:44",
      "content": "<p>Thanks for the links</p>",
      "votes": null,
      "replies": [
        {
          "id": 908292,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "06/30/2020 13:41:29",
          "content": "<p>You are welcome <a href=\"/ashkhagan\">@ashkhagan</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 909512,
      "author_name": "mdselimreza",
      "author_url": "",
      "post_date": "06/30/2020 16:17:48",
      "content": "<p>Thank you Ishan for sharing!</p>",
      "votes": null,
      "replies": [
        {
          "id": 909666,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "06/30/2020 18:14:59",
          "content": "<p>Welcome <a href=\"/mdselimreza\">@mdselimreza</a> . I hope it helps you.</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 909859,
      "author_name": "krishvanapalli",
      "author_url": "",
      "post_date": "06/30/2020 21:41:10",
      "content": "<p>Thanks <a href=\"/ishandutta\">@ishandutta</a> for the links, they were helpful!</p>",
      "votes": null,
      "replies": [
        {
          "id": 910947,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "07/01/2020 13:17:29",
          "content": "<p>You are welcome <a href=\"/krishvanapalli\">@krishvanapalli</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 910357,
      "author_name": "shyamrn",
      "author_url": "",
      "post_date": "07/01/2020 05:46:20",
      "content": "<p>Thanks <a href=\"/ishandutta\">@ishandutta</a>  for sharing. Good collection!!!</p>",
      "votes": null,
      "replies": [
        {
          "id": 910944,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "07/01/2020 13:17:06",
          "content": "<p>Welcome <a href=\"/shyamrn\">@shyamrn</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 910899,
      "author_name": "",
      "author_url": "",
      "post_date": "07/01/2020 12:42:56",
      "content": "<p>Thanks !!</p>",
      "votes": null,
      "replies": [
        {
          "id": 910942,
          "author_name": "ishandutta",
          "author_url": "",
          "post_date": "07/01/2020 13:16:27",
          "content": "<p>Welcome <a href=\"/wusihan\">@wusihan</a> </p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "890769": "1. [Deep Convolutional Neural Network to Detect J-UNIWARD](https://arxiv.org/ftp/arxiv/papers/1704/1704.08378.pdf)\n2. [CNN-based Steganalysis and Parametric Adversarial Embedding: a Game-Theoretic Framework](https://arxiv.org/pdf/1906.00697.pdf)\n3. [Pooled Steganalysis in JPEG: how to deal with the spreading strategy?](https://arxiv.org/pdf/1906.11525.pdf)\n4. [Deep Learning in steganography and steganalysis from 2015 to 2018](https://arxiv.org/pdf/1904.01444.pdf)\n5. [JPEG Steganalysis Based on DenseNet](https://arxiv.org/pdf/1711.09335.pdf)\n6. [Large-scale JPEG image steganalysis using hybrid deep-learning framework](https://arxiv.org/pdf/1611.03233.pdf)\n7. [Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key Erratum note](https://arxiv.org/pdf/1605.07946.pdf)",
    "893742": "good collection!",
    "894655": "Thanks @nandinivineeth",
    "907915": "Thanks for the links",
    "908292": "You are welcome @ashkhagan",
    "909512": "Thank you Ishan for sharing!",
    "909666": "Welcome @mdselimreza . I hope it helps you.",
    "909859": "Thanks @ishandutta for the links, they were helpful!",
    "910357": "Thanks @ishandutta  for sharing. Good collection!!!",
    "910899": "Thanks !!",
    "910942": "Welcome @wusihan",
    "910944": "Welcome @shyamrn",
    "910947": "You are welcome @krishvanapalli",
    "1235093": "Thank you."
  },
  "source": "meta"
}