{
  "id": 307810,
  "title": "Some relevant papers on using deep learning for identifying Herbarium specimens",
  "url": "/competitions/herbarium-2022-fgvc9/discussion/307810",
  "author_name": "Tuan Nguyen-Sy",
  "post_date": "2022-02-15T17:42:43.441000",
  "votes": 10,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Below is a list of some relevant papers on using deep learning for identifying Herbarium specimens:</p>\n<ul>\n<li><p><a href=\"https://arxiv.org/ftp/arxiv/papers/2104/2104.08732.pdf\" target=\"_blank\">Application of Computer Vision and Machine Learning for Digitized Herbarium Specimens: A Systematic Literature Review</a></p></li>\n<li><p><a href=\"https://bmcecolevol.biomedcentral.com/track/pdf/10.1186/s12862-017-1014-z.pdf\" target=\"_blank\">Going deeper in the automated identification of Herbarium specimens</a></p></li>\n<li><p><a href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328654/\" target=\"_blank\">Plants meet machines: Prospects in machine learning for plant biology</a></p></li>\n<li><p><a href=\"https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.11367\" target=\"_blank\">LeafMachine: Using machine learning to automate leaf trait extraction from digitized herbarium specimens</a></p></li>\n<li><p><a href=\"https://link.springer.com/content/pdf/10.1186/s12862-016-0827-5.pdf\" target=\"_blank\">Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification</a></p></li>\n<li><p><a href=\"https://www.sciencedirect.com/science/article/abs/pii/S1574954121000340\" target=\"_blank\">Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy</a></p></li>\n<li><p><a href=\"https://watermark.silverchair.com/biaa044.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAtIwggLOBgkqhkiG9w0BBwagggK_MIICuwIBADCCArQGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMrG4x0F9LFzt-Rh3mAgEQgIIChaERDomoOKYPTnwTE9vbPOYoEf9Zps_68XnuLxkLqTTUfMjndO90SMGcZ5ARslHVUzap3_RqaSwHBiFEbbzPwQDTSRnbdERbgi9Ia6wlN_tN85_tn2wFgyd-Pb5OHeq1wwtYK0OwK-bTHDzOwqR6XCigHM0MzDaUkJNkCTSkPyL3OPkObwwFxT11FFwzs2tPDT9F5UFyDclDZgIKeylzkKzE2jLaaSXzaUpJAI_gCkQpSyrLPBBEcn5bSh6aUlG2qUiU7sdsfpdKUrpOtINSCK2x5HOSqksjOGz1bp_xayBqiziJoWpkNe1z03NPL3mfMnq-O19YBuHuNOIkdVj_QnFqP8REsLK-GXvC6lTqD1n2Dy-2yH8UjQxLNxTvqU90g0tBFm_cDywzYde_QslIxRuXzS-B6_F5D7jfJJdan3KYIcHY1y5we084UiW4UORtRxo7HQIETbNhaWlLY1whXLQ0yiyD_CA7llhayfXqT3mUVYTi0LfG1QxluvXdTub4TNYZMDCaMU4ANuTZcvHul5Eih4G2YUWFdekNFKtXPsuhQpuwGlFoW0qpDvw4Ln0zT2MmGAvHd9dkKAcahHMuxtI0IuSpQobFVTIRSU5QUfg6g8KuLcEpGV-sF6LlT44HZKlxyejdK3NmnC5W9Y1ACaS2lZyblXIEiMVTCdm3xYDxK9hsmIuplNU_MnXmmUCFqKUnS8m5A0bDLY3XlF_p5Urky-Tmt6xuMQSGUuoQhvImn2LA2LT86gc6cErjHVGoIN3xpX_8fQ9ykhug6V5mkfXEkxyTrFTKrM8m1Imurg5uMPDxVP2NHOUvN2o1DWwaBM-cc7HD3GxjN8XGDbkKeoR7zRbNzQ\" target=\"_blank\">Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research</a></p></li>\n</ul>",
  "messages": [
    {
      "id": 1691948,
      "postDate": "2022-02-15T17:42:43.440Z",
      "content": "<p>Below is a list of some relevant papers on using deep learning for identifying Herbarium specimens:</p>\n<ul>\n<li><p><a href=\"https://arxiv.org/ftp/arxiv/papers/2104/2104.08732.pdf\" target=\"_blank\">Application of Computer Vision and Machine Learning for Digitized Herbarium Specimens: A Systematic Literature Review</a></p></li>\n<li><p><a href=\"https://bmcecolevol.biomedcentral.com/track/pdf/10.1186/s12862-017-1014-z.pdf\" target=\"_blank\">Going deeper in the automated identification of Herbarium specimens</a></p></li>\n<li><p><a href=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328654/\" target=\"_blank\">Plants meet machines: Prospects in machine learning for plant biology</a></p></li>\n<li><p><a href=\"https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.11367\" target=\"_blank\">LeafMachine: Using machine learning to automate leaf trait extraction from digitized herbarium specimens</a></p></li>\n<li><p><a href=\"https://link.springer.com/content/pdf/10.1186/s12862-016-0827-5.pdf\" target=\"_blank\">Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification</a></p></li>\n<li><p><a href=\"https://www.sciencedirect.com/science/article/abs/pii/S1574954121000340\" target=\"_blank\">Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy</a></p></li>\n<li><p><a href=\"https://watermark.silverchair.com/biaa044.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAtIwggLOBgkqhkiG9w0BBwagggK_MIICuwIBADCCArQGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMrG4x0F9LFzt-Rh3mAgEQgIIChaERDomoOKYPTnwTE9vbPOYoEf9Zps_68XnuLxkLqTTUfMjndO90SMGcZ5ARslHVUzap3_RqaSwHBiFEbbzPwQDTSRnbdERbgi9Ia6wlN_tN85_tn2wFgyd-Pb5OHeq1wwtYK0OwK-bTHDzOwqR6XCigHM0MzDaUkJNkCTSkPyL3OPkObwwFxT11FFwzs2tPDT9F5UFyDclDZgIKeylzkKzE2jLaaSXzaUpJAI_gCkQpSyrLPBBEcn5bSh6aUlG2qUiU7sdsfpdKUrpOtINSCK2x5HOSqksjOGz1bp_xayBqiziJoWpkNe1z03NPL3mfMnq-O19YBuHuNOIkdVj_QnFqP8REsLK-GXvC6lTqD1n2Dy-2yH8UjQxLNxTvqU90g0tBFm_cDywzYde_QslIxRuXzS-B6_F5D7jfJJdan3KYIcHY1y5we084UiW4UORtRxo7HQIETbNhaWlLY1whXLQ0yiyD_CA7llhayfXqT3mUVYTi0LfG1QxluvXdTub4TNYZMDCaMU4ANuTZcvHul5Eih4G2YUWFdekNFKtXPsuhQpuwGlFoW0qpDvw4Ln0zT2MmGAvHd9dkKAcahHMuxtI0IuSpQobFVTIRSU5QUfg6g8KuLcEpGV-sF6LlT44HZKlxyejdK3NmnC5W9Y1ACaS2lZyblXIEiMVTCdm3xYDxK9hsmIuplNU_MnXmmUCFqKUnS8m5A0bDLY3XlF_p5Urky-Tmt6xuMQSGUuoQhvImn2LA2LT86gc6cErjHVGoIN3xpX_8fQ9ykhug6V5mkfXEkxyTrFTKrM8m1Imurg5uMPDxVP2NHOUvN2o1DWwaBM-cc7HD3GxjN8XGDbkKeoR7zRbNzQ\" target=\"_blank\">Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research</a></p></li>\n</ul>",
      "rawMarkdown": "Below is a list of some relevant papers on using deep learning for identifying Herbarium specimens:\n\n* [Application of Computer Vision and Machine Learning for Digitized Herbarium Specimens: A Systematic Literature Review](https://arxiv.org/ftp/arxiv/papers/2104/2104.08732.pdf)\n\n* [Going deeper in the automated identification of Herbarium specimens](https://bmcecolevol.biomedcentral.com/track/pdf/10.1186/s12862-017-1014-z.pdf)\n\n* [Plants meet machines: Prospects in machine learning for plant biology](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328654/)\n\n* [LeafMachine: Using machine learning to automate leaf trait extraction from digitized herbarium specimens](https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.11367)\n\n* [Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification](https://link.springer.com/content/pdf/10.1186/s12862-016-0827-5.pdf)\n\n* [Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy] (https://www.sciencedirect.com/science/article/abs/pii/S1574954121000340)\n\n* [Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research](https://watermark.silverchair.com/biaa044.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAtIwggLOBgkqhkiG9w0BBwagggK_MIICuwIBADCCArQGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMrG4x0F9LFzt-Rh3mAgEQgIIChaERDomoOKYPTnwTE9vbPOYoEf9Zps_68XnuLxkLqTTUfMjndO90SMGcZ5ARslHVUzap3_RqaSwHBiFEbbzPwQDTSRnbdERbgi9Ia6wlN_tN85_tn2wFgyd-Pb5OHeq1wwtYK0OwK-bTHDzOwqR6XCigHM0MzDaUkJNkCTSkPyL3OPkObwwFxT11FFwzs2tPDT9F5UFyDclDZgIKeylzkKzE2jLaaSXzaUpJAI_gCkQpSyrLPBBEcn5bSh6aUlG2qUiU7sdsfpdKUrpOtINSCK2x5HOSqksjOGz1bp_xayBqiziJoWpkNe1z03NPL3mfMnq-O19YBuHuNOIkdVj_QnFqP8REsLK-GXvC6lTqD1n2Dy-2yH8UjQxLNxTvqU90g0tBFm_cDywzYde_QslIxRuXzS-B6_F5D7jfJJdan3KYIcHY1y5we084UiW4UORtRxo7HQIETbNhaWlLY1whXLQ0yiyD_CA7llhayfXqT3mUVYTi0LfG1QxluvXdTub4TNYZMDCaMU4ANuTZcvHul5Eih4G2YUWFdekNFKtXPsuhQpuwGlFoW0qpDvw4Ln0zT2MmGAvHd9dkKAcahHMuxtI0IuSpQobFVTIRSU5QUfg6g8KuLcEpGV-sF6LlT44HZKlxyejdK3NmnC5W9Y1ACaS2lZyblXIEiMVTCdm3xYDxK9hsmIuplNU_MnXmmUCFqKUnS8m5A0bDLY3XlF_p5Urky-Tmt6xuMQSGUuoQhvImn2LA2LT86gc6cErjHVGoIN3xpX_8fQ9ykhug6V5mkfXEkxyTrFTKrM8m1Imurg5uMPDxVP2NHOUvN2o1DWwaBM-cc7HD3GxjN8XGDbkKeoR7zRbNzQ)\n\n",
      "votes": 10
    },
    {
      "id": 1692074,
      "postDate": "2022-02-15T19:40:47.010Z",
      "content": "<p>Thanks for sharing, <a href=\"https://www.kaggle.com/sytuannguyen\" target=\"_blank\">@sytuannguyen</a>! Looking forward to seeing some innovative solutions, possibly inspired by some of these papers. :) </p>",
      "rawMarkdown": "Thanks for sharing, @sytuannguyen! Looking forward to seeing some innovative solutions, possibly inspired by some of these papers. :) ",
      "votes": 1
    },
    {
      "id": 1697777,
      "postDate": "2022-02-19T20:41:15.103Z",
      "content": "<p>Thank you for sharing! Super helpful!</p>",
      "rawMarkdown": "Thank you for sharing! Super helpful!"
    },
    {
      "id": 1692764,
      "postDate": "2022-02-16T08:11:21.747Z",
      "content": "<p>Thank you for sharing, <a href=\"https://www.kaggle.com/sytuannguyen\" target=\"_blank\">@sytuannguyen</a>! </p>",
      "rawMarkdown": "Thank you for sharing, @sytuannguyen! ",
      "votes": 1
    }
  ],
  "comments": [
    {
      "id": 1692074,
      "author_name": "Roshan Ram",
      "author_url": "",
      "post_date": "2022-02-15T19:40:47.010000",
      "content": "<p>Thanks for sharing, <a href=\"https://www.kaggle.com/sytuannguyen\" target=\"_blank\">@sytuannguyen</a>! Looking forward to seeing some innovative solutions, possibly inspired by some of these papers. :) </p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 1697777,
      "author_name": "John Park",
      "author_url": "",
      "post_date": "2022-02-19T20:41:15.103000",
      "content": "<p>Thank you for sharing! Super helpful!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 1692764,
      "author_name": "Vadim Irtlach",
      "author_url": "",
      "post_date": "2022-02-16T08:11:21.747000",
      "content": "<p>Thank you for sharing, <a href=\"https://www.kaggle.com/sytuannguyen\" target=\"_blank\">@sytuannguyen</a>! </p>",
      "votes": 1,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1691948": "Below is a list of some relevant papers on using deep learning for identifying Herbarium specimens:\n\n* [Application of Computer Vision and Machine Learning for Digitized Herbarium Specimens: A Systematic Literature Review](https://arxiv.org/ftp/arxiv/papers/2104/2104.08732.pdf)\n\n* [Going deeper in the automated identification of Herbarium specimens](https://bmcecolevol.biomedcentral.com/track/pdf/10.1186/s12862-017-1014-z.pdf)\n\n* [Plants meet machines: Prospects in machine learning for plant biology](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328654/)\n\n* [LeafMachine: Using machine learning to automate leaf trait extraction from digitized herbarium specimens](https://bsapubs.onlinelibrary.wiley.com/doi/pdf/10.1002/aps3.11367)\n\n* [Computer vision applied to herbarium specimens of German trees: testing the future utility of the millions of herbarium specimen images for automated identification](https://link.springer.com/content/pdf/10.1186/s12862-016-0827-5.pdf)\n\n* [Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy] (https://www.sciencedirect.com/science/article/abs/pii/S1574954121000340)\n\n* [Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research](https://watermark.silverchair.com/biaa044.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAtIwggLOBgkqhkiG9w0BBwagggK_MIICuwIBADCCArQGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMrG4x0F9LFzt-Rh3mAgEQgIIChaERDomoOKYPTnwTE9vbPOYoEf9Zps_68XnuLxkLqTTUfMjndO90SMGcZ5ARslHVUzap3_RqaSwHBiFEbbzPwQDTSRnbdERbgi9Ia6wlN_tN85_tn2wFgyd-Pb5OHeq1wwtYK0OwK-bTHDzOwqR6XCigHM0MzDaUkJNkCTSkPyL3OPkObwwFxT11FFwzs2tPDT9F5UFyDclDZgIKeylzkKzE2jLaaSXzaUpJAI_gCkQpSyrLPBBEcn5bSh6aUlG2qUiU7sdsfpdKUrpOtINSCK2x5HOSqksjOGz1bp_xayBqiziJoWpkNe1z03NPL3mfMnq-O19YBuHuNOIkdVj_QnFqP8REsLK-GXvC6lTqD1n2Dy-2yH8UjQxLNxTvqU90g0tBFm_cDywzYde_QslIxRuXzS-B6_F5D7jfJJdan3KYIcHY1y5we084UiW4UORtRxo7HQIETbNhaWlLY1whXLQ0yiyD_CA7llhayfXqT3mUVYTi0LfG1QxluvXdTub4TNYZMDCaMU4ANuTZcvHul5Eih4G2YUWFdekNFKtXPsuhQpuwGlFoW0qpDvw4Ln0zT2MmGAvHd9dkKAcahHMuxtI0IuSpQobFVTIRSU5QUfg6g8KuLcEpGV-sF6LlT44HZKlxyejdK3NmnC5W9Y1ACaS2lZyblXIEiMVTCdm3xYDxK9hsmIuplNU_MnXmmUCFqKUnS8m5A0bDLY3XlF_p5Urky-Tmt6xuMQSGUuoQhvImn2LA2LT86gc6cErjHVGoIN3xpX_8fQ9ykhug6V5mkfXEkxyTrFTKrM8m1Imurg5uMPDxVP2NHOUvN2o1DWwaBM-cc7HD3GxjN8XGDbkKeoR7zRbNzQ)\n\n",
    "1692074": "Thanks for sharing, @sytuannguyen! Looking forward to seeing some innovative solutions, possibly inspired by some of these papers. :) ",
    "1697777": "Thank you for sharing! Super helpful!",
    "1692764": "Thank you for sharing, @sytuannguyen! "
  }
}