2020
DOI: 10.1016/j.neucom.2019.10.055
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Tensor cross-view quadratic discriminant analysis for kinship verification in the wild

Abstract: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, a… Show more

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Cited by 25 publications
(2 citation statements)
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“…Bessaoudi et al ( 2019 ) extracted the high-order representations of facial features. And (Laiadi et al, 2020 ) used Tensor Cross-view Quadratic Discriminant Analysis (TXQDA) method. They use the feature mapping method to learn low-dimension tensors to reduce the factors brought by age and gender.…”
Section: Kinship Verification From Still Imagesmentioning
confidence: 99%
“…Bessaoudi et al ( 2019 ) extracted the high-order representations of facial features. And (Laiadi et al, 2020 ) used Tensor Cross-view Quadratic Discriminant Analysis (TXQDA) method. They use the feature mapping method to learn low-dimension tensors to reduce the factors brought by age and gender.…”
Section: Kinship Verification From Still Imagesmentioning
confidence: 99%
“…Dornaika et al used MNRML to train the two features, FC7 layers of VGG-F and VGG-Face for the purpose of kinship verification. Laiadi et al proposed TXQDA [13] method to train LPQ and BSIF features using ten scales.…”
Section: Introductionmentioning
confidence: 99%