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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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Bibliografische Detailangaben
Hauptverfasser: Hidayaturrahman, Agung Trisetyarso, Iman Herwidiana Kartowisastro, Widodo Budiharto
Format: Artigo
Sprache:Inglês
Veröffentlicht: IEEE 2024-01-01
Schriftenreihe:IEEE Access
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Online-Zugang:https://ieeexplore.ieee.org/document/10685350/
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