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Low-Rank Deep Convolutional Neural Network for Multitask Learning
In this paper, we propose a novel multitask learning method based on the deep convolutional network. The proposed deep network has four convolutional layers, three max-pooling layers, and two parallel fully connected layers. To adjust the deep network to multitask learning problem, we propose to lea...
Autores principales: | Su, Fang, Shang, Hai-Yang, Wang, Jing-Yan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545796/ https://www.ncbi.nlm.nih.gov/pubmed/31236107 http://dx.doi.org/10.1155/2019/7410701 |
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