Investigating Catastrophic Forgetting of Deep Learning Models Within Office 31 Dataset
Deep learning models have shown impressive performance in various tasks. However, they are prone to a phenomenon called catastrophic forgetting. This means they do not remember what they have learned when training on new tasks. In this research paper, we focus on catastrophic forgetting within the c...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
IEEE
2024-01-01
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| Schriftenreihe: | IEEE Access |
| Schlagworte: | |
| Online-Zugang: | https://ieeexplore.ieee.org/document/10685350/ |
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