Multi-Task Learning with Task-Specific Feature Filtering in Low-Data Condition
Multi-task learning is a computationally efficient method to solve multiple tasks in one multi-task model, instead of multiple single-task models. MTL is expected to learn both diverse and shareable visual features from multiple datasets. However, MTL performances usually do not outperform single-ta...
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/a66ea26763d343aab655f260efa48ecc |
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