Dataset Open Access

Polymers Hyperspectral Imaging

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

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    <dct:title>Polymers Hyperspectral Imaging</dct:title>
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    <dcat:keyword>Hyperspectral Image Classification</dcat:keyword>
    <dcat:keyword>Plastic</dcat:keyword>
    <dcat:keyword>Polymers</dcat:keyword>
    <dcat:keyword>E-waste</dcat:keyword>
    <dcat:keyword>Deep Learning</dcat:keyword>
    <dcat:keyword>Machine Learning</dcat:keyword>
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    <dct:description>&lt;p&gt;&lt;strong&gt;Investigating State of the Art Hyperspectral Imaging Classification Models for Plastic Types Identification&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Polymers Dataset&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Description:&lt;/p&gt; &lt;p&gt;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. &lt;/p&gt; &lt;p&gt;Two sample batches were investigated:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;reference polymers of known composition and dimensions (15 X 10) cm, commonly found in e-waste.&lt;/li&gt; &lt;li&gt;shredded pieces of polymers with sizes ranging from (0.3–4) cm.&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Data Format&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;HSI data: each hyperspectral data cube is accompanied by a data file and a .hdr file.&lt;/li&gt; &lt;li&gt;Ground truth mask: .png file (only for multi samples scenes)&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Folder Organization&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Polymers &lt;ul&gt; &lt;li&gt;Test &lt;ul&gt; &lt;li&gt;HSI: .dat &amp; .hdr&lt;/li&gt; &lt;li&gt;Ground truth mask: test.png&lt;/li&gt; &lt;li&gt;False colour representation of the scene: .png&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;li&gt;Train &lt;ul&gt; &lt;li&gt;HSI_ : 3 different scans of reference samples scanned&lt;/li&gt; &lt;li&gt;PC, PE, PET, PP: Hyperspectral cubes (11x11x450) .hdr &amp; .dat&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Data Classes in Masks&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Masks contain 1 to 6 segmentation classes: &lt;ul&gt; &lt;li&gt;1: "PP"&lt;/li&gt; &lt;li&gt;2: "Black Plastic"&lt;/li&gt; &lt;li&gt;3: "PVC"&lt;/li&gt; &lt;li&gt;4: "PET"&lt;/li&gt; &lt;li&gt;5: "ABS"&lt;/li&gt; &lt;li&gt;6: "PE"&lt;/li&gt; &lt;/ul&gt; &lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Code Repository&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;To facilitate reading and working with the data, Python codes are available on the GitHub repository:&lt;/p&gt; &lt;p&gt;https://github.com/hifexplo&lt;/p&gt; &lt;p&gt;https://github.com/Elias-Arbash&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Citation&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;If you use this dataset, please cite the following article: (To be filled once published)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Contact&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;For further information or inquiries, please visit our website:&lt;/p&gt; &lt;p&gt;https://www.iexplo.space/&lt;/p&gt; &lt;p&gt;Contact Email: e.arbash@hzdr.de&lt;/p&gt;</dct:description>
    <dct:description xml:lang="">The HSI dataset of the work: INVESTIGATING STATE OF THE ART HYPERSPECTRAL IMAGING CLASSIFICATION MODELS FOR PLASTIC TYPES IDENTIFICATION</dct:description>
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Publication date:
December 8, 2024
DOI:
10.14278/rodare.3390

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Keyword(s):
Hyperspectral Image Classification Plastic Polymers E-waste Deep Learning Machine Learning
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