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- W4225868051 abstract "In today’s world, with the rise of infectious diseases, proper hand-washing has become essential, particularly in hospitals and breeding grounds for pathogens. However, even in these places, pseudo dirty hand spots remain, which may be a significant vector for nosocomial diseases if proper and effective hand washing does not occur. That is why hand-washing in hospitals needs to be automated to detect hygiene without facing the problem due to skin color and brightness. While most methods deal with hand-wash compliance using video processing or sensors, we propose a Hygiene Maintenance CNN (HMCNN) Model for detecting hand-washing compliance by breaking the video into frames and utilizing transfer learning. The HMCNN model is used to get better results with 93.38% accuracy against tested consistent data than the pre-existing model. The proposed model can check the WHO guidelines for hand-washing and notify the user if it is not done correctly, helping set up a medical sector hand-wash sanitizing monitoring system." @default.
- W4225868051 created "2022-05-05" @default.
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- W4225868051 date "2021-12-17" @default.
- W4225868051 modified "2023-10-01" @default.
- W4225868051 title "Hand-Wash Sanitization Compliance Monitoring CNN Model To Maintain The Hygiene" @default.
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- W4225868051 doi "https://doi.org/10.1109/icac3n53548.2021.9725483" @default.
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