Dynamic margin contrastive learning for open-set recognition in long-tailed sonar imagery

Dynamic margin contrastive learning for open-set recognition in long-tailed sonar imagery

Abstract Long-tail distribution and open-set recognition remain significant challenges in sonar image classification. This study introduces Dynamic Margin Contrastive Learning (DMCL), a novel framework that simultaneously addresses both issues through adaptive margin adjustment and uncertainty-aware...

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Bibliographic Details
Main Authors: Yu Lin, Shuiyuan He, Weidong Luo
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Open-set recognition
Long-tailed distribution
Sonar image classification
Dynamic margin
Contrastive learning
Uncertainty estimation
Online Access:https://doi.org/10.1038/s41598-025-04877-6
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https://doi.org/10.1038/s41598-025-04877-6

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