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Residual Quantity in Percentage of Factory Machines Using Computer Vision and Mathematical Methods

Computer Vision and Pattern Recognition 2022-02-15 v3
Authors: Seunghyeon Kim , Jihoon Ryoo , Dongyeob Lee , Youngho Kim
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Abstract

Computer vision has been thriving since AI development was gaining thrust. Using deep learning techniques has been the most popular way which computer scientists thought the solution of. However, deep learning techniques tend to show lower performance than manual processing. Using deep learning is not always the answer to a problem related to computer vision.

Keywords

computer vision deep learning factory machines residual quantity mathematical methods

Cite

@article{arxiv.2111.05080,
  title  = {Residual Quantity in Percentage of Factory Machines Using Computer Vision and Mathematical Methods},
  author = {Seunghyeon Kim and Jihoon Ryoo and Dongyeob Lee and Youngho Kim},
  journal= {arXiv preprint arXiv:2111.05080},
  year   = {2022}
}

Comments

4 pages, 13 figures

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