April 7, 2025 Dataset Open Access

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

JSON Export

{
  "created": "2025-04-07T13:08:01.690481+00:00", 
  "doi": "10.14278/rodare.3668", 
  "revision": 430, 
  "files": [
    {
      "size": 4690701426, 
      "bucket": "6aec6e44-765a-4a91-b1bb-041d6f7f2710", 
      "key": "Electrolyzers-HSI.zip", 
      "type": "zip", 
      "links": {
        "self": "https://rodare.hzdr.de/api/files/6aec6e44-765a-4a91-b1bb-041d6f7f2710/Electrolyzers-HSI.zip"
      }, 
      "checksum": "md5:637ae2f393c630e762353bc1ab7b17d7"
    }
  ], 
  "stats": {
    "volume": 234535071300.0, 
    "unique_downloads": 36.0, 
    "version_unique_downloads": 36.0, 
    "unique_views": 1101.0, 
    "downloads": 50.0, 
    "version_unique_views": 1101.0, 
    "version_views": 1158.0, 
    "version_downloads": 50.0, 
    "version_volume": 234535071300.0, 
    "views": 1158.0
  }, 
  "metadata": {
    "doc_id": "1", 
    "access_right_category": "success", 
    "communities": [
      {
        "id": "hzdr"
      }, 
      {
        "id": "rodare"
      }
    ], 
    "license": {
      "id": "CC-BY-4.0"
    }, 
    "title": "Electrolyzers-HSI: Close-Range Multi-Scene Hyperspectral Imaging Benchmark Dataset", 
    "creators": [
      {
        "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie - University of Antwerb", 
        "orcid": "0009-0000-2187-9171", 
        "name": "Arbash, Elias"
      }, 
      {
        "orcid": "0000-0001-6782-6753", 
        "name": "Afifi, Ahmed Jamal Mohammaed"
      }, 
      {
        "affiliation": "National School of Applied Sciences of Oujda", 
        "name": "Belahsen, Ymane"
      }, 
      {
        "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
        "orcid": "0000-0001-7210-1132", 
        "name": "Fuchs, Margret"
      }, 
      {
        "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
        "orcid": "0000-0003-1203-741X", 
        "name": "Ghamisi, Pedram"
      }, 
      {
        "affiliation": "University of Antwerp", 
        "orcid": "0000-0003-2447-4772", 
        "name": "Scheunders, Paul"
      }, 
      {
        "affiliation": "Helmholtz-Institut Freiberg f\u00fcr Ressourcentechnologie", 
        "orcid": "0000-0002-4383-473X", 
        "name": "Gloaguen, Richard"
      }
    ], 
    "publication_date": "2025-04-07", 
    "pub_id": "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"
    ], 
    "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>", 
    "access_right": "open", 
    "doi": "10.14278/rodare.3668", 
    "related_identifiers": [
      {
        "relation": "isIdenticalTo", 
        "scheme": "url", 
        "identifier": "https://www.hzdr.de/publications/Publ-41192"
      }, 
      {
        "relation": "isVersionOf", 
        "scheme": "doi", 
        "identifier": "10.14278/rodare.3667"
      }
    ], 
    "resource_type": {
      "type": "dataset", 
      "title": "Dataset"
    }, 
    "relations": {
      "version": [
        {
          "count": 1, 
          "is_last": true, 
          "last_child": {
            "pid_value": "3668", 
            "pid_type": "recid"
          }, 
          "index": 0, 
          "parent": {
            "pid_value": "3667", 
            "pid_type": "recid"
          }
        }
      ]
    }
  }, 
  "links": {
    "badge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.3668.svg", 
    "doi": "https://doi.org/10.14278/rodare.3668", 
    "conceptbadge": "https://rodare.hzdr.de/badge/doi/10.14278/rodare.3667.svg", 
    "conceptdoi": "https://doi.org/10.14278/rodare.3667", 
    "bucket": "https://rodare.hzdr.de/api/files/6aec6e44-765a-4a91-b1bb-041d6f7f2710", 
    "html": "https://rodare.hzdr.de/record/3668", 
    "latest": "https://rodare.hzdr.de/api/records/3668", 
    "latest_html": "https://rodare.hzdr.de/record/3668"
  }, 
  "updated": "2025-11-17T08:00:21.652127+00:00", 
  "owners": [
    840
  ], 
  "conceptdoi": "10.14278/rodare.3667", 
  "id": 3668, 
  "conceptrecid": "3667"
}