<italic>T</italic>-Center: A Novel Feature Extraction Approach Towards Large-Scale Iris Recognition

<italic>T</italic>-Center: A Novel Feature Extraction Approach Towards Large-Scale Iris Recognition

For large-scale iris recognition tasks, the determination of classification thresholds remains a challenging task, especially in practical applications where sample space is growing rapidly. Due to the complexity of iris samples, the classification threshold is difficult to determine with the increa...

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Bibliographic Details
Main Authors: Yifeng Chen, Cheng Wu, Yiming Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Biometric
iris recognition
large-scale dataset
softmax loss
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">T</italic>-center loss
Online Access:https://ieeexplore.ieee.org/document/8995585/

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https://ieeexplore.ieee.org/document/8995585/

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