ConnectomeNet: A Unified Deep Neural Network Modeling Framework for Multi-Task Learning
Despite recent advances in deep neural networks (DNNs), multi-task learning has not been able to utilize DNNs thoroughly. The current method of DNN design for a single task requires considerable skill in deciding many architecture parameters a priori before training begins. However, extending it to...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10076453/ |