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Abstract
The article analyzes methods for detecting face masks in access control and management systems, and also presents a method of convolution neural networks for detecting face masks using deep machine learning technology. Face mask images in the form of a neural network model were trained on the generated database, and performance metrics were determined using metrics such as model accuracy, F1-score, precision and recall.
Keywords
access control system, biometric system, machine learning, deep learning, neural networks, evaluation metrics.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Abdukadirov Bakhtiyor, & Abdukadirova Gulbahor. (2023). APPROACH TO DETECTION OF FACE OCCLUSION IN ACCESS CONTROL SYSTEMS. American Journal of Pedagogical and Educational Research, 9, 44–48. Retrieved from https://americanjournal.org/index.php/ajper/article/view/416