LDMP-RENet: Reducing intra-class differences for metal surface defect few-shot semantic segmentation.
Given their fast generalization capability for unseen classes and segmentation ability at pixel scale, models based on few-shot segmentation perform well in solving data insufficiency problems during metal defect detection and in delineating refined objects under industrial scenarios. Extant researche...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318553 |
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