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An Analysis of Face Recognition under Face Mask Occlusions

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dc.contributor.author Hemathilaka, S
dc.contributor.author Aponso, A
dc.date.accessioned 2025-04-11T08:38:43Z
dc.date.available 2025-04-11T08:38:43Z
dc.date.issued 2021
dc.identifier.citation Hemathilaka, S. and Aponso, A. (2021a) ‘An Analysis of Face Recognition under Face Mask Occlusions’, in Machine Learning Techniques and Data Science. 2nd International Conference on Machine Learning Techniques and Data Science (MLDS 2021), Academy and Industry Research Collaboration Center (AIRCC), pp. 41–48. Available at: https://doi.org/10.5121/csit.2021.111804. en_US
dc.identifier.other https://doi.org/10.5121/csit.2021.111804.
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2227
dc.description.abstract The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features. en_US
dc.language.iso en en_US
dc.publisher Academy and Industry Research Collaboration Center (AIRCC) en_US
dc.subject Deep Learning en_US
dc.subject Face recodnition en_US
dc.subject CNN en_US
dc.title An Analysis of Face Recognition under Face Mask Occlusions en_US
dc.type Article en_US


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