| Autor: |
José Armando Fragoso-Mandujano, Madain Pérez-Patricio, Jorge Luis Camas-Anzueto, Hector Daniel Vázquez-Delgado, Eduardo Chandomí-Castellanos, Yair Gonzalez-Baldizón, Julio Alberto Guzman-Rabasa, Julio Cesar Martinez-Morgan, Luis Enrique Guillén-Ruíz |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 12, Iss 4, p 2071 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app12042071 |
| Popis: |
Due to the increasing need for continuous use of face masks caused by COVID-19, it is essential to evaluate the filtration quality that each face mask provides. In this research, an estimation method based on thermal image processing was developed; the main objective was to evaluate the effectiveness of different face masks while being used during breathing. For the acquisition of heat distribution images, a thermographic imaging system was built; moreover, a deep learning model detected the leakage percentage of each face mask with a mAP of 0.9345, recall of 0.842 and F1-score of 0.82. The results obtained from this research revealed that the filtration effectiveness depended on heat loss through the manufacturing material; the proposed estimation method is simple, fast, and can be replicated and operated by people who are not experts in the computer field. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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