Critical Evaluation of LOCO dataset with Machine Learning

  title={Critical Evaluation of LOCO dataset with Machine Learning},
  author={Recep Savaş and Johannes Hinckeldeyn},
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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  • Petru SovianyRadu Tudor Ionescu
  • Computer Science
    2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
  • 2018
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