Hierarchical Feature Attention Learning Network for Detecting Object and Discriminative Parts in Fine-Grained Visual Classification
This paper proposes a novel hierarchical feature attention learning network for improved fine-grained visual classification (FGVC). Existing fine-grained classification methods rely heavily on attention mechanisms to differentiate minute details of similar objects. These mechanisms often assume that...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10854460/ |
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