Classification of Long-Tailed Data Based on Bilateral-Branch Generative Network with Time-Supervised Strategy
In the face of the long-tailed data distribution that widely exists in real-world datasets, this paper proposes a bilateral-branch generative network model. The data of the second branch is constructed by resampling the generative network training method to improve the data quality. A bilateral-bran...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/8667868 |
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