January 29, 2024 Dataset Open Access

Arbash, Elias; Fuchs, Margret; Rasti, Behnood; Lorenz, Sandra; Ghamisi, Pedram; Gloaguen, Richard

JSON-LD (schema.org) Export

{
  "distribution": [
    {
      "@type": "DataDownload", 
      "contentUrl": "https://rodare.hzdr.de/api/files/671920b9-68a5-4a82-98d1-c696f25e497c/PCBDataset.zip", 
      "fileFormat": "zip"
    }
  ], 
  "isPartOf": [
    {
      "@type": "CreativeWork", 
      "@id": "https://www.hzdr.de/publications/Publ-38529"
    }
  ], 
  "name": "PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards", 
  "keywords": [
    "circular economy", 
    "automated data processing", 
    "optical sensors", 
    "recycling", 
    "e-waste", 
    "printed circuit board", 
    "hyperspectral", 
    "dataset", 
    "RGB", 
    "conveyor belt", 
    "sensors", 
    "machine learning", 
    "deep learning", 
    "PCBVision", 
    "open-source data", 
    "digitalization"
  ], 
  "description": "<p><strong>PCB-Vision Dataset</strong></p>\n\n<p>Description:</p>\n\n<p>The PCB-Vision dataset is a multiscene RGB-Hyperspectral benchmark dataset comprising 53 Printed Circuit Boards (PCBs). The RGB images are collected using a Teledyne Dalsa C4020 camera on a conveyor belt, while hyperspectral images (HSI) are acquired with a Specim FX10 spectrometer. The HSI data contains 224 bands in the VNIR range [400 - 1000]nm.</p>\n\n<p><strong>Data Format</strong></p>\n\n<ul>\n\t<li>RGB Images: .png files</li>\n\t<li>PCB Masks: .jpg files</li>\n\t<li>HSI Data: Each hyperspectral data cube is accompanied by a data file and a .hdr file.</li>\n</ul>\n\n<p><strong>Folder Organization</strong></p>\n\n<ul>\n\t<li>PCBVision\n\t<ul>\n\t\t<li>HSI/\n\t\t<ul>\n\t\t\t<li>53 subfolders (one for each PCB)</li>\n\t\t\t<li>&#39;General_masks&#39; folder for &#39;General&#39; segmentation ground truth</li>\n\t\t\t<li>&#39;Monoseg_masks&#39; folder for &#39;Monoseg&#39; segmentation ground truth</li>\n\t\t\t<li>&#39;PCB_Masks&#39; folder for masks of the 53 PCBs in the hyperspectral cube</li>\n\t\t</ul>\n\t\t</li>\n\t\t<li>RGB/\n\t\t<ul>\n\t\t\t<li>53 .jpg images</li>\n\t\t\t<li>&#39;General&#39;&nbsp;folder for RGB images &#39;General&#39; segmentation ground truth</li>\n\t\t\t<li>&#39;Monoseg_masks&#39; folder for RGB images &#39;Monoseg&#39; segmentation ground truth</li>\n\t\t</ul>\n\t\t</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p><strong>Data Classes in Masks</strong></p>\n\n<ul>\n\t<li>Masks (both &#39;General&#39; and &#39;Monoseg&#39;) contain 1 to 4 segmentation classes:\n\t<ul>\n\t\t<li>0: &quot;Others&quot;</li>\n\t\t<li>1: &quot;IC&quot;</li>\n\t\t<li>2: &quot;Capacitors&quot;</li>\n\t\t<li>3: &quot;Connectors&quot;</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p><strong>Code Repository</strong></p>\n\n<p>To facilitate reading and working with the data, Python codes are available on the GitHub repository:</p>\n\n<p>https://github.com/hifexplo/PCBVision</p>\n\n<p><strong>Citation</strong></p>\n\n<p>If you use this dataset, please cite the following article:</p>\n\n<p><strong>Word</strong>:</p>\n\n<p>Arbash, Elias, Fuchs, Margret, Rasti, Behnood, Lorenz, Sandra, Ghamisi, Pedram, &amp; Gloaguen, Richard. (2024). PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards (Version 1) [Data set]. Rodare. <a href=\"http://doi.org/10.14278/rodare.2704\">http://doi.org/10.14278/rodare.2704</a></p>\n\n<p><strong>Latex:</strong></p>\n\n<p>@article{arbash2024pcb, title={PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards}, author={Arbash, Elias and Fuchs, Margret and Rasti, Behnood and Lorenz, Sandra and Ghamisi, Pedram and Gloaguen, Richard}, journal={arXiv preprint arXiv:2401.06528}, year={2024} }</p>\n\n<p><strong>Contact</strong></p>\n\n<p>For further information or inquiries, please visit our website:</p>\n\n<p>https://www.iexplo.space/</p>\n\n<p>Contact Email: e.arbash@hzdr.de</p>", 
  "datePublished": "2024-01-29", 
  "creator": [
    {
      "name": "Arbash, Elias", 
      "@type": "Person", 
      "affiliation": "Helmholtz Institute Freiberg for Resource Technology"
    }, 
    {
      "name": "Fuchs, Margret", 
      "@type": "Person", 
      "@id": "https://orcid.org/0000-0001-7210-1132", 
      "affiliation": "Helmholtz Institute Freiberg for Resource Technology"
    }, 
    {
      "name": "Rasti, Behnood", 
      "@type": "Person"
    }, 
    {
      "name": "Lorenz, Sandra", 
      "@type": "Person", 
      "@id": "https://orcid.org/0000-0001-8464-2331", 
      "affiliation": "Helmholtz Institute Freiberg for Resource Technology"
    }, 
    {
      "name": "Ghamisi, Pedram", 
      "@type": "Person", 
      "@id": "https://orcid.org/0000-0003-1203-741X", 
      "affiliation": "Helmholtz Institute Freiberg for Resource Technology"
    }, 
    {
      "name": "Gloaguen, Richard", 
      "@type": "Person", 
      "@id": "https://orcid.org/0000-0002-4383-473X", 
      "affiliation": "Helmholtz Institute Freiberg for Resource Technology"
    }
  ], 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "@id": "https://doi.org/10.14278/rodare.2704", 
  "sameAs": [
    "https://www.hzdr.de/publications/Publ-38684"
  ], 
  "@type": "Dataset", 
  "identifier": "https://doi.org/10.14278/rodare.2704", 
  "version": "1", 
  "@context": "https://schema.org/", 
  "url": "https://rodare.hzdr.de/record/2704"
}