The Do's and Don'ts for Increasing the Accuracy of Face Recognition on VGGFace2 Dataset

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dc.authoridErbir, Muhammed Ali/0000-0002-2438-0744
dc.contributor.authorErbir, Muhammed Ali
dc.contributor.authorUnver, Halil Murat
dc.date.accessioned2025-01-21T16:45:00Z
dc.date.available2025-01-21T16:45:00Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn this study, developments in face recognition are examined. Some methods are presented to increase the accuracy rate in face recognition by using transfer learning with VGGFace2 dataset and 4 different CNN models. While some of these tested offers decreased the accuracy rate, some of them increased. Effects of histogram balancing, expanding the training data, extracting the effect of non-facial portions of images and vertically aligning images on the accuracy rate were determined and compared to the accuracy rates of original images. As the optimal solution, transfer learning from the InceptionV3 model was preferred, vertical positioning was made, and an accuracy rate of 95.47% was achieved when 10% of the images were used for testing and 90% for training in a 100 people subset of VGGFace2 dataset. In LFW, one of the widely used datasets in the literature, an accuracy rate of 100% has been achieved by exceeding the highest accuracy achieved so far and all images in the LFW database have been recognized without any problems.
dc.identifier.doi10.1007/s13369-021-05693-6
dc.identifier.endpage8911
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue9
dc.identifier.startpage8901
dc.identifier.urihttps://doi.org/10.1007/s13369-021-05693-6
dc.identifier.urihttps://hdl.handle.net/20.500.12587/25568
dc.identifier.volume46
dc.identifier.wosWOS:000649238000002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofArabian Journal For Science and Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241229
dc.subjectFace recognition; Face verification; Biometric verification; Deep learning; Image processing; VGGFace2 dataset
dc.titleThe Do's and Don'ts for Increasing the Accuracy of Face Recognition on VGGFace2 Dataset
dc.typeArticle

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