TWO-WAY METRIC LEARNING WITH MAJORITY AND MINORITY SUBSETS FOR CLASSIFICATION OF LARGE EXTREMELY IMBALANCED FACE DATASET

TWO-WAY METRIC LEARNING WITH MAJORITY AND MINORITY SUBSETS FOR CLASSIFICATION OF LARGE EXTREMELY IMBALANCED FACE DATASET

This paper proposes a new learning methodology involving deep features and two-way metric learning for large, extremely imbalanced face datasets where the number of minority classes and the imbalance ratio are both very high. The problem arises because the faces of some celebrities, being more popul...

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Detalles Bibliográficos
Autores principales: Ashu Kaushik, Seba Susan
Formato: article
Lenguaje:EN
Publicado: Scientific Research Support Fund of Jordan (SRSF) and Princess Sumaya University for Technology (PSUT) 2021
Materias:
face recognition
metric learning
vgg-face
deep learning
imbalanced learning
extremely imbalanced dataset
Information technology
T58.5-58.64
Electronic computers. Computer science
QA75.5-76.95
Acceso en línea:https://doaj.org/article/7e26b2cef55244e5a6807707f93b2e55
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https://doaj.org/article/7e26b2cef55244e5a6807707f93b2e55

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