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<titleInfo><title>Synthetic Training Dataset for Real-World Terminal Strip Object Detection</title></titleInfo>



<note type="internalNote">CHe</note>



<name type="personal">
  <namePart type="given">Nico</namePart>
  <namePart type="family">Baumgart</namePart>
  <role><roleTerm type="text">author</roleTerm> </role><identifier type="local">88090</identifier></name>
<name type="personal">
  <namePart type="given">Markus</namePart>
  <namePart type="family">Lange-Hegermann</namePart>
  <role><roleTerm type="text">author</roleTerm> </role><identifier type="local">71761</identifier></name>
<name type="personal">
  <namePart type="given">Mike</namePart>
  <namePart type="family">Mücke</namePart>
  <role><roleTerm type="text">author</roleTerm> </role></name>







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  <namePart></namePart>
  <identifier type="local">DEP5015</identifier>
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<abstract lang="eng">

This dataset provides synthetic training data for the real-world industrial application of terminal strip object detection to investigate the sim-to-real generalization performance of modern object detectors based on state-of-the-art image synthesis methods. It consists of 30.000 randomly generated synthetic images of terminal strips covering 36 different terminal blocks in five colors and additional accessories such as plug-in bridges, test adapters, end covers and markings. Except from the markings and the DIN rail all objects of the terminal strips are labeled with a bounding box and the respective object class for supervised learning. Additionally, 300 real images of terminal strips were taken and manually labeled for the real-world test.

If you use this datset for your research, please consider citing this: Investigation of the Impact of Synthetic Training Data in the Industrial Application of Terminal Strip Object Detection
</abstract>

<originInfo><publisher>Zenodo</publisher><dateIssued encoding="w3cdtf">2024</dateIssued>
</originInfo>

<subject><topic>Object Detection</topic><topic>Image Synthesis</topic><topic>Domain Randomization</topic><topic>Domain Gap</topic><topic>Terminal Strip</topic>
</subject>


<relatedItem type="host"><identifier type="doi">10.5281/ZENODO.16080102</identifier>
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<bibliographicCitation>
<ieee>N. Baumgart, M. Lange-Hegermann, and M. Mücke, &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo, 2024. doi: &lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;10.5281/ZENODO.16080102&lt;/a&gt;.</ieee>
<bjps>&lt;b&gt;Baumgart N, Lange-Hegermann M and Mücke M&lt;/b&gt; (2024) &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo.</bjps>
<mla>Baumgart, Nico, et al. &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo, 2024, &lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;https://doi.org/10.5281/ZENODO.16080102&lt;/a&gt;.</mla>
<apa>Baumgart, N., Lange-Hegermann, M., &amp;#38; Mücke, M. (2024). &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo. &lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;https://doi.org/10.5281/ZENODO.16080102&lt;/a&gt;</apa>
<van>Baumgart N, Lange-Hegermann M, Mücke M. Synthetic Training Dataset for Real-World Terminal Strip Object Detection. Zenodo; 2024.</van>
<short>N. Baumgart, M. Lange-Hegermann, M. Mücke, Synthetic Training Dataset for Real-World Terminal Strip Object Detection, Zenodo, 2024.</short>
<havard>N. Baumgart, M. Lange-Hegermann, M. Mücke, Synthetic Training Dataset for Real-World Terminal Strip Object Detection, Zenodo, 2024.</havard>
<din1505-2-1>&lt;span style=&quot;font-variant:small-caps;&quot;&gt;Baumgart, Nico&lt;/span&gt; ; &lt;span style=&quot;font-variant:small-caps;&quot;&gt;Lange-Hegermann, Markus&lt;/span&gt; ; &lt;span style=&quot;font-variant:small-caps;&quot;&gt;Mücke, Mike&lt;/span&gt;: &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt; : Zenodo, 2024</din1505-2-1>
<ufg>&lt;b&gt;Baumgart, Nico/Lange-Hegermann, Markus/Mücke, Mike&lt;/b&gt;: Synthetic Training Dataset for Real-World Terminal Strip Object Detection, o. O. 2024.</ufg>
<ama>Baumgart N, Lange-Hegermann M, Mücke M. &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo; 2024. doi:&lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;10.5281/ZENODO.16080102&lt;/a&gt;</ama>
<chicago>Baumgart, Nico, Markus Lange-Hegermann, and Mike Mücke. &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo, 2024. &lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;https://doi.org/10.5281/ZENODO.16080102&lt;/a&gt;.</chicago>
<chicago-de>Baumgart, Nico, Markus Lange-Hegermann und Mike Mücke. 2024. &lt;i&gt;Synthetic Training Dataset for Real-World Terminal Strip Object Detection&lt;/i&gt;. Zenodo. doi:&lt;a href=&quot;https://doi.org/10.5281/ZENODO.16080102&quot;&gt;10.5281/ZENODO.16080102&lt;/a&gt;, .</chicago-de>
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