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  <doc>
    <id>2444</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>5</pageLast>
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    <edition/>
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    <volume/>
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    <title language="eng">Combining BLOB-Detection and MLP to Detect and Identify Plastics in an Environmental Matrix</title>
    <abstract language="eng">Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix.</abstract>
    <parentTitle language="eng">2023 IEEE Sensors Applications Symposium (SAS)</parentTitle>
    <identifier type="doi">10.1109/SAS58821.2023.10254171</identifier>
    <enrichment key="opus.import.data">@inproceedingswohlschlager_combining_2023, title = Combining BLOB-Detection and MLP to Detect and Identify Plastics in an Environmental Matrix, doi = 10.1109/SAS58821.2023.10254171, booktitle = 2023 IEEE Sensors Applications Symposium (SAS), author = Wohlschläger, Maximilian and Khan, Yamna and Leiter, Nina and Versen, Martin and Löder, Martin and Laforsch, Christian, year = 2023, keywords = Fluorescence, Plastics, FD-FLIM, Neural networks, MLP, blob detection, Classification algorithms, Dogs, fluorescence lifetime, plastics identification, Soil, Thresholding (Imaging), pages = 01–05,</enrichment>
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    <author>Maximilian Wohlschläger</author>
    <author>Yamna Khan</author>
    <author>Nina Leiter</author>
    <author>Martin Versen</author>
    <author>Martin Löder</author>
    <author>Christian Laforsch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fluorescence</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Plastics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FD-FLIM</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MLP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>blob detection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Classification algorithms</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Dogs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>fluorescence lifetime</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>plastics identification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Soil</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Thresholding (Imaging)</value>
    </subject>
  </doc>
  <doc>
    <id>2438</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
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    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Development of a BLOB-detection algorithm based on DoG to detect Plastic in an environmental matrix using FD-FLIM</title>
    <abstract language="eng">The direct identification of plastics in an environmental matrix is heavily researched. We successfully developed a BLOB-detection algorithm based on differences of Gaussians to identify HDPE particles in an artificial environmental matrix using FD-FLIM.</abstract>
    <parentTitle language="eng">Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES)</parentTitle>
    <identifier type="doi">10.1364/ES.2023.EW4E.4</identifier>
    <enrichment key="opus.import.data">@inproceedingswohlschlager_development_2023, title = Development of a BLOB-detection algorithm based on DoG to detect Plastic in an environmental matrix using FD-FLIM, url = https://opg.optica.org/abstract.cfm?URI=ES-2023-EW4E.4, doi = 10.1364/ES.2023.EW4E.4, abstract = The direct identification of plastics in an environmental matrix is heavily researched. We successfully developed a BLOB-detection algorithm based on differences of Gaussians to identify HDPE particles in an artificial environmental matrix using FD-FLIM., booktitle = Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES), publisher = Optica Publishing Group, author = Wohlschläger, Maximilian and Khan, Yamna and Leiter, Nina and Versen, Martin and Löder, Martin and Laforsch, Christian, year = 2023, note = Journal Abbreviation: Optica Sensing Congress 2023 (AIS, FTS, HISE, Sensors, ES), keywords = Diode lasers, Fluorescence lifetime imaging, Phase shift, Neural networks, Optical filters, Spatial resolution, pages = EW4E.4,</enrichment>
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    <author>Maximilian Wohlschläger</author>
    <author>Yamna Khan</author>
    <author>Nina Leiter</author>
    <author>Martin Versen</author>
    <author>Martin Löder</author>
    <author>Christian Laforsch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Diode lasers</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fluorescence lifetime imaging</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Phase shift</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optical filters</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Spatial resolution</value>
    </subject>
  </doc>
  <doc>
    <id>2443</id>
    <completedYear>2023</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>6</pageLast>
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    <issue/>
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    <type>conferenceobject</type>
    <publisherName/>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Comparative Analysis of Fluorescence Properties of Post-Consumer Wood Using FD-FLIM</title>
    <abstract language="eng">The FD-FLIM technique has a high potential for automated post-consumer wood sorting. A problem of analysing post-consumer wood fluorescence properties is the uncertainty of the post-consumer wood category as the origin of the samples are unknown. In this study, the fluorescence properties of actual post-consumer wood is compared with prepared wood samples. The post-consumer wood samples display slightly different fluorescence intensities and lifetimes due to environmental influences and a higher sample diversity. For improved training of evaluation algorithms for post-consumer wood sorting, the prepared sample set should be extended or the post-consumer wood should be additionally analysed in the laboratory.</abstract>
    <parentTitle language="eng">2023 IEEE Sensors Applications Symposium (SAS)</parentTitle>
    <identifier type="doi">10.1109/SAS58821.2023.10254052</identifier>
    <enrichment key="opus.import.data">@inproceedingsleiter_comparative_2023, title = Comparative Analysis of Fluorescence Properties of Post-Consumer Wood Using FD-FLIM, doi = 10.1109/SAS58821.2023.10254052, booktitle = 2023 IEEE Sensors Applications Symposium (SAS), author = Leiter, Nina and Wohlschläger, Maximilian and Dietlmeier, Maximilian and Versen, Martin and Löder, Martin and Laforsch, Christian, year = 2023, keywords = fluorescence, Fluorescence, Neural networks, fluorescence properties, Moisture, post-consumer wood, Sensors, Training, Uncertainty, Visualization, waste wood, pages = 1–6,</enrichment>
    <enrichment key="opus.import.dataHash">md5:72865d2f2abde5cc0635ac4f1d2848f3</enrichment>
    <enrichment key="opus.import.date">2024-05-27T12:38:19+00:00</enrichment>
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    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <author>Nina Leiter</author>
    <author>Maximilian Wohlschläger</author>
    <author>Maximilian Dietlmeier</author>
    <author>Martin Versen</author>
    <author>Martin Löder</author>
    <author>Christian Laforsch</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>fluorescence</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fluorescence</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Neural networks</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>fluorescence properties</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Moisture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>post-consumer wood</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Training</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Uncertainty</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Visualization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>waste wood</value>
    </subject>
  </doc>
</export-example>
