Face mask recognition based on object detection

Earlier in 2019, a novel coronavirus pneumonia outbreak occurred in most countries and regions of the world. Thus, judging whether individuals are wearing masks or not has become an important part of entrance inspection in many places. In this paper, object detection in Google Cloud Platform's AutoML is used to implement mask detection. 1,000 from these 2,000 pictures are selected to refine the dataset for training, including 500 faces with masks and 500 faces without masks. After training, the accuracy achieves 94% and the map achieves 97.3%, which can meet the requirements of practical application. What’s more, tflite is used to deploy the model on the edge, to realize the application of the model in the real scenes.

• Publication year

  2021

• Venue

  Other Conferences

• Publication date

  2021-06-01

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1117/12.2600460
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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