December 8, 2024 Dataset Open Access

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

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  <dc:creator>Arbash, Elias</dc:creator>
  <dc:creator>de Lima Ribeiro, Andrea</dc:creator>
  <dc:creator>Rizaldy, Aldino</dc:creator>
  <dc:creator>Fuchs, Margret</dc:creator>
  <dc:creator>Ghamisi, Pedram</dc:creator>
  <dc:creator>Scheunders, Paul</dc:creator>
  <dc:creator>Gloaguen, Richard</dc:creator>
  <dc:date>2024-12-08</dc:date>
  <dc:description>Investigating State of the Art Hyperspectral Imaging Classification Models for Plastic Types Identification&#13;
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Polymers Dataset&#13;
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Description:&#13;
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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 [400–2500] nm range using an AisaFENIX (Spectral Imaging Ltd, Oulu, Finland) spectrometer. &#13;
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Two sample batches were investigated:&#13;
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&#13;
 reference polymers of known composition and dimensions (15 X 10) cm, commonly found in e-waste.&#13;
 shredded pieces of polymers with sizes ranging from (0.3–4) cm.&#13;
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Data Format&#13;
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 HSI data: each hyperspectral data cube is accompanied by a data file and a .hdr file.&#13;
 Ground truth mask: .png file (only for multi samples scenes)&#13;
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Folder Organization&#13;
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 Polymers&#13;
 &#13;
  Test&#13;
  &#13;
   HSI: .dat &amp; .hdr&#13;
   Ground truth mask: test.png&#13;
   False colour representation of the scene: .png&#13;
  &#13;
  &#13;
  Train&#13;
  &#13;
   HSI_ : 3 different scans of reference samples scanned&#13;
   PC, PE, PET, PP: Hyperspectral cubes (11x11x450) .hdr &amp; .dat&#13;
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  &#13;
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Data Classes in Masks&#13;
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&#13;
 Masks contain 1 to 6 segmentation classes:&#13;
 &#13;
  1: "PP"&#13;
  2: "Black Plastic"&#13;
  3: "PVC"&#13;
  4: "PET"&#13;
  5: "ABS"&#13;
  6: "PE"&#13;
 &#13;
 &#13;
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Code Repository&#13;
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To facilitate reading and working with the data, Python codes are available on the GitHub repository:&#13;
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https://github.com/hifexplo&#13;
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https://github.com/Elias-Arbash&#13;
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Citation&#13;
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If you use this dataset, please cite the following article: (To be filled once published)&#13;
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Contact&#13;
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For further information or inquiries, please visit our website:&#13;
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https://www.iexplo.space/&#13;
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Contact Email: e.arbash@hzdr.de</dc:description>
  <dc:description>The HSI dataset of the work: INVESTIGATING STATE OF THE ART HYPERSPECTRAL IMAGING CLASSIFICATION MODELS FOR PLASTIC TYPES IDENTIFICATION</dc:description>
  <dc:identifier>https://rodare.hzdr.de/record/3390</dc:identifier>
  <dc:identifier>10.14278/rodare.3390</dc:identifier>
  <dc:identifier>oai:rodare.hzdr.de:3390</dc:identifier>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-40592</dc:relation>
  <dc:relation>url:https://www.hzdr.de/publications/Publ-40590</dc:relation>
  <dc:relation>doi:10.14278/rodare.3389</dc:relation>
  <dc:relation>url:https://rodare.hzdr.de/communities/hzdr</dc:relation>
  <dc:relation>url:https://rodare.hzdr.de/communities/rodare</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Hyperspectral Image Classification</dc:subject>
  <dc:subject>Plastic</dc:subject>
  <dc:subject>Polymers</dc:subject>
  <dc:subject>E-waste</dc:subject>
  <dc:subject>Deep Learning</dc:subject>
  <dc:subject>Machine Learning</dc:subject>
  <dc:title>Polymers Hyperspectral Imaging</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>