RobustDeiT: Noise-Robust Vision Transformers for Medical Image Classification
Effective classification of medical images is vital for accurate diagnosis and treatment, but noisy datasets remain a significant challenge, obscuring critical features and leading to unreliable predictions. To address this, we propose RobustDeiT, a noise-robust architecture based on the Data-effic...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Slovenian Society for Stereology and Quantitative Image Analysis
2025-06-01
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| Series: | Image Analysis and Stereology |
| Subjects: | |
| Online Access: | https://www.ias-iss.org/ojs/IAS/article/view/3561 |
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