April 7, 2025 Dataset Open Access

Arbash, Elias; Afifi, Ahmed Jamal Mohammaed; Belahsen, Ymane; Fuchs, Margret; Ghamisi, Pedram; Scheunders, Paul; Gloaguen, Richard

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{
  "name": "Electrolyzers-HSI: Close-Range Multi-Scene Hyperspectral Imaging Benchmark Dataset", 
  "description": "<p><strong>Electrolyzers-HSI Dataset</strong></p>\r\n\r\n<p>Description:</p>\r\n\r\n<p>The Electrolyzers-HSI dataset is a multiscene RGB-Hyperspectral benchmark dataset comprising 55 scene of shredded Electrolyzers samples. The RGB images are collected using a Teledyne Dalsa C4020 camera on a conveyor belt, while hyperspectral images (HSI) are acquired with a FENIX spectrometer. The HSI data contains 450 bands in the VNIR and SWIR range [400 - 2500]nm.</p>\r\n\r\n<p><strong>Data Format</strong></p>\r\n\r\n<ul>\r\n <li>RGB Images: .jpg files</li>\r\n <li>Ground Truth (GT): .png files. They appear black since the values are between 0 and 5. Correct visualization is done via script.</li>\r\n <li>HSI Data: Each hyperspectral data cube .img file is accompanied by a .hdr file.</li>\r\n</ul>\r\n\r\n<p><strong>Folder Organization</strong></p>\r\n\r\n<ul>\r\n <li><strong>Electrolyzers-HSI: </strong>55 subfolders\u00a0\r\n\r\n <ul>\r\n  <li>1/\r\n  <ul>\r\n   <li>\u2019GT.png\u2019 file for segmentation ground truth</li>\r\n   <li>\u2018HSI.img\u2019 and \u2018HSI.hdr\u2019 files for HSI data cube</li>\r\n   <li>\u2018RGB.jpg\u2019 file for the RGB image</li>\r\n  </ul>\r\n  </li>\r\n  <li>2/\r\n  <ul>\r\n   <li>\u2019GT.png\u2019 file for segmentation ground truth</li>\r\n   <li>\u2018HSI.img\u2019 and \u2018HSI.hdr\u2019 files for HSI data cube</li>\r\n   <li>\u2018RGB.jpg\u2019 file for the RGB image</li>\r\n  </ul>\r\n  </li>\r\n  <li>3/4/5/6/ \u2026 :Same structure for all rest of folders</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 0 to 5 segmentation classes:\r\n <ul>\r\n  <li>0: background</li>\r\n  <li>1: \u201cMESH\u201d</li>\r\n  <li>2: \u201cSteel_Cathode\u201d</li>\r\n  <li>3: \"Steel_Anode\u201d</li>\r\n  <li>4: \u201cHTEL_Anode\u201d</li>\r\n  <li>5: \u201cHTEL_Cathode\u201d</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><strong>Citation</strong></p>\r\n\r\n<p>If you use this dataset, please cite the following article:</p>\r\n\r\n<p><strong>Word</strong>:</p>\r\n\r\n<p><strong>Latex:</strong></p>", 
  "datePublished": "2025-04-07", 
  "@context": "https://schema.org/", 
  "creator": [
    {
      "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie - University of Antwerb", 
      "name": "Arbash, Elias", 
      "@id": "https://orcid.org/0009-0000-2187-9171", 
      "@type": "Person"
    }, 
    {
      "name": "Afifi, Ahmed Jamal Mohammaed", 
      "@id": "https://orcid.org/0000-0001-6782-6753", 
      "@type": "Person"
    }, 
    {
      "affiliation": "National School of Applied Sciences of Oujda", 
      "name": "Belahsen, Ymane", 
      "@type": "Person"
    }, 
    {
      "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
      "name": "Fuchs, Margret", 
      "@id": "https://orcid.org/0000-0001-7210-1132", 
      "@type": "Person"
    }, 
    {
      "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
      "name": "Ghamisi, Pedram", 
      "@id": "https://orcid.org/0000-0003-1203-741X", 
      "@type": "Person"
    }, 
    {
      "affiliation": "University of Antwerp", 
      "name": "Scheunders, Paul", 
      "@id": "https://orcid.org/0000-0003-2447-4772", 
      "@type": "Person"
    }, 
    {
      "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
      "name": "Gloaguen, Richard", 
      "@id": "https://orcid.org/0000-0002-4383-473X", 
      "@type": "Person"
    }
  ], 
  "url": "https://rodare.hzdr.de/record/3668", 
  "@type": "Dataset", 
  "@id": "https://doi.org/10.14278/rodare.3668", 
  "distribution": [
    {
      "contentUrl": "https://rodare.hzdr.de/api/files/6aec6e44-765a-4a91-b1bb-041d6f7f2710/Electrolyzers-HSI.zip", 
      "fileFormat": "zip", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.14278/rodare.3668", 
  "sameAs": [
    "https://www.hzdr.de/publications/Publ-41192"
  ], 
  "keywords": [
    "circular economy", 
    "automated data processing", 
    "optical sensors", 
    "Hyperspectral Imaging", 
    "HSI", 
    "Hyperspectral Imaging classification", 
    "recycling", 
    "E-waste", 
    "hyperspectral imaging dataset", 
    "RGB dataset", 
    "conveyor belt", 
    "sensors", 
    "spectrometers", 
    "machine learning", 
    "deep learning", 
    "Electrolyzers", 
    "open source", 
    "digitalization", 
    "Transformers"
  ], 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode"
}