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Automated Quality Inspection Using Computer Vision: a Review

EasyChair Preprint no. 7824

12 pagesDate: April 21, 2022


In the context of manufacturing, ensuring the highest quality of the product can be an expensive task; because of, dealing with defective products, slowdowns of the production line, intermittent visual inspections, and high cost of uptime and downtime, plus customer complaints after the product is shipped. That is why the computer vision system uses machine learning to spotdefects in real-time on product specifications. In this paper, we introduce the newly developed automated inspection techniques, presenting an overview based on the statistical studies applied in the manufacturing environment, and on computer vision Stages. The paper lists the most recent machine learning and deep learning algorithms applied in manufacturing to detect defects of the products.

Keyphrases: computer vision, deep learning, machine learning, Manufacturing, quality control, Transfer Learning

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Ghizlane Belkhedar and Abdelouahid Lyhyaoui},
  title = {Automated Quality Inspection Using Computer Vision: a Review},
  howpublished = {EasyChair Preprint no. 7824},

  year = {EasyChair, 2022}}
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