@misc{13824,
  abstract     = {{

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
}},
  author       = {{Baumgart, Nico and Lange-Hegermann, Markus and Mücke, Mike}},
  keywords     = {{Object Detection, Image Synthesis, Domain Randomization, Domain Gap, Terminal Strip}},
  publisher    = {{Zenodo}},
  title        = {{{Synthetic Training Dataset for Real-World Terminal Strip Object Detection}}},
  doi          = {{10.5281/ZENODO.16080102}},
  year         = {{2024}},
}