Adaptive Hierarchical Similarity Metric Learning with Noisy Labels

Deep Metric Learning (DML) plays a critical role in various machine learning tasks. However, most existing deep metric learning methods with binary similarity are sensitive to noisy labels, which are widely present in real-world data. Since these noisy labels often cause a severe performance degrada...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 32; p. 1
Main Authors:	Yan, Jiexi, Luo, Lei, Deng, Cheng, Huang, Heng
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation models Cognitive tasks Consistency Contrastive Augmentation Deep Metric Learning Geometry Hierarchical Similarity Hyperbolic Geometry Labels Machine learning Measurement Noise measurement Noisy Labels Performance degradation Robustness Similarity Task analysis Training
ISSN:	1057-7149, 1941-0042, 1941-0042
Online Access:	Get full text
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