Deep transfer metric learning

Deep transfer metric learning

Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption doesn't hold in many real visual recognition applications, especially when samples are captured across...

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Bibliographic Details
Main Authors: Hu, Junlin, Lu, Jiwen, Tan, Yap Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2016
Subjects:
Face
Face recognition
Learning systems
Machine learning
Training
Visualization
Measurement
Online Access:https://hdl.handle.net/10356/80552
http://hdl.handle.net/10220/40552

Internet

https://hdl.handle.net/10356/80552
http://hdl.handle.net/10220/40552

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