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Unified Complementary Learning with Feature Perturbation for Semi-Supervised Learning

Semi-supervised learning has attracted widespread attention due to its ability to utilize both labeled and unlabeled data, leading to significant progress in recent years. Conventional semi-supervised learning approaches often rely on a strategy that combines weak and strong image-level augmentation...

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Principais autores: Ke Wang, Jie Yang, Yunfei Guo, Anke Xue
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2026-01-01
Colecção:Algorithms
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Acesso em linha:https://www.mdpi.com/1999-4893/19/1/56
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