Improving Accuracy of Face Recognition in the Era of Mask-Wearing: An Evaluation of a Pareto-Optimized FaceNet Model with Data Preprocessing Techniques

The paper presents an evaluation of a Pareto-optimized FaceNet model with data preprocessing techniques to improve the accuracy of face recognition in the era of mask-wearing. The COVID-19 pandemic has led to an increase in mask-wearing, which poses a challenge for face recognition systems. The prop...

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Hlavní autoři:	Damilola Akingbesote, Ying Zhan, Rytis Maskeliūnas, Robertas Damaševičius
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2023-06-01
Edice:	Algorithms
Témata:	Pareto optimization face recognition mask-wearing methods for segmentation of faces synthetic datasets FaceNet
On-line přístup:	https://www.mdpi.com/1999-4893/16/6/292
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