Discriminative deep metric learning for face verification in the wild

Discriminative deep metric learning for face verification in the wild

This paper presents a new discriminative deep metric learning (DDML) method for face verification in the wild. Different from existing metric learning-based face verification methods which aim to learn a Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-c...

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書目詳細資料
Main Authors:	Hu, Junlin, Lu, Jiwen, Tan, Yap Peng
其他作者:	School of Electrical and Electronic Engineering
格式:	Conference or Workshop Item
語言:	English
出版:	2015
主題:	DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
在線閱讀:	https://hdl.handle.net/10356/100336 http://hdl.handle.net/10220/25706
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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