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Polymers Hyperspectral Imaging

Arbash, Elias; de Lima Ribeiro, Andrea; Rizaldy, Aldino; Fuchs, Margret; Ghamisi, Pedram; Scheunders, Paul; Gloaguen, Richard


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    "title": "Polymers Hyperspectral Imaging", 
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    "notes": "The HSI dataset of the work: INVESTIGATING STATE OF THE ART HYPERSPECTRAL IMAGING CLASSIFICATION MODELS FOR PLASTIC TYPES IDENTIFICATION", 
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    "creators": [
      {
        "name": "Arbash, Elias", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0009-0000-2187-9171"
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      {
        "name": "de Lima Ribeiro, Andrea", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0000-0003-0096-3627"
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      {
        "name": "Rizaldy, Aldino", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0009-0004-4138-7878"
      }, 
      {
        "name": "Fuchs, Margret", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0000-0001-7210-1132"
      }, 
      {
        "name": "Ghamisi, Pedram", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0000-0003-1203-741X"
      }, 
      {
        "name": "Scheunders, Paul", 
        "affiliation": "University of Antwerp", 
        "orcid": "0000-0003-2447-4772"
      }, 
      {
        "name": "Gloaguen, Richard", 
        "affiliation": "Helmholtz Institute Freiberg", 
        "orcid": "0000-0002-4383-473X"
      }
    ], 
    "keywords": [
      "Hyperspectral Image Classification", 
      "Plastic", 
      "Polymers", 
      "E-waste", 
      "Deep Learning", 
      "Machine Learning"
    ], 
    "publication_date": "2024-12-08", 
    "license": {
      "id": "CC-BY-4.0"
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    "description": "<p><strong>Investigating State of the Art Hyperspectral Imaging Classification Models for Plastic Types Identification</strong></p>\r\n\r\n<p><strong>Polymers Dataset</strong></p>\r\n\r\n<p>Description:</p>\r\n\r\n<p>The polymers dataset is a multiscene Hyperspectral benchmark dataset comprising of reference polymer samples and shredded polymer samples in the visible to short-wave infrared, capturing 450 bands within the [400\u20132500] nm range using an AisaFENIX (Spectral Imaging Ltd, Oulu, Finland) spectrometer.\u00a0</p>\r\n\r\n<p>Two sample batches were investigated:</p>\r\n\r\n<ul>\r\n <li>reference polymers of known composition and dimensions (15 X 10) cm, commonly found in e-waste.</li>\r\n <li>shredded pieces of polymers with sizes ranging from (0.3\u20134) cm.</li>\r\n</ul>\r\n\r\n<p><strong>Data Format</strong></p>\r\n\r\n<ul>\r\n <li>HSI data: each hyperspectral data cube is accompanied by a data file and a .hdr file.</li>\r\n <li>Ground truth mask: .png file (only for multi samples scenes)</li>\r\n</ul>\r\n\r\n<p><strong>Folder Organization</strong></p>\r\n\r\n<ul>\r\n <li>Polymers\r\n <ul>\r\n  <li>Test\r\n  <ul>\r\n   <li>HSI:\u00a0.dat & .hdr</li>\r\n   <li>Ground truth mask: test.png</li>\r\n   <li>False colour representation of the scene: .png</li>\r\n  </ul>\r\n  </li>\r\n  <li>Train\r\n  <ul>\r\n   <li>HSI_ : 3 different scans of reference samples scanned</li>\r\n   <li>PC, PE, PET, PP: Hyperspectral cubes (11x11x450) .hdr & .dat</li>\r\n  </ul>\r\n  </li>\r\n </ul>\r\n </li>\r\n</ul>\r\n\r\n<p><strong>Data Classes in Masks</strong></p>\r\n\r\n<ul>\r\n <li>Masks contain 1 to 6 segmentation classes:\r\n <ul>\r\n  <li>1: \"PP\"</li>\r\n  <li>2: \"Black Plastic\"</li>\r\n  <li>3: \"PVC\"</li>\r\n  <li>4: \"PET\"</li>\r\n  <li>5: \"ABS\"</li>\r\n  <li>6: \"PE\"</li>\r\n </ul>\r\n </li>\r\n</ul>\r\n\r\n<p><strong>Code Repository</strong></p>\r\n\r\n<p>To facilitate reading and working with the data, Python codes are available on the GitHub repository:</p>\r\n\r\n<p>https://github.com/hifexplo</p>\r\n\r\n<p>https://github.com/Elias-Arbash</p>\r\n\r\n\r\n\r\n<p><strong>Citation</strong></p>\r\n\r\n<p>If you use this dataset, please cite the following article: (To be filled once published)</p>\r\n\r\n\r\n\r\n<p><strong>Contact</strong></p>\r\n\r\n<p>For further information or inquiries, please visit our website:</p>\r\n\r\n<p>https://www.iexplo.space/</p>\r\n\r\n<p>Contact Email: e.arbash@hzdr.de</p>", 
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