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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Autores principales: Sang-woo Lee, Ryong Lee, Min-seok Seo, Jong-chan Park, Hyeon-cheol Noh, Jin-gi Ju, Rae-young Jang, Gun-woo Lee, Myung-seok Choi, Dong-geol Choi
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/a66ea26763d343aab655f260efa48ecc
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