Critical Evaluation of LOCO dataset with Machine Learning

@article{Sava2022CriticalEO,
  title={Critical Evaluation of LOCO dataset with Machine Learning},
  author={Recep Savaş and Johannes Hinckeldeyn},
  journal={ArXiv},
  year={2022},
  volume={abs/2209.13499}
}
Purpose: Object detection is rapidly evolving through machine learning technology in automation systems. Well prepared data is necessary to train the algorithms. Accordingly, the objective of this paper is to describe a re-evaluation of the so-called Logistics Objects in Context (LOCO) dataset, which is the first dataset for object detection in the field of intralogistics. Methodology: We use an experimental research approach with three steps to evaluate the LOCO dataset. Firstly, the images on… 

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