Reducing catastrophic forgetting of incremental learning in the absence of rehearsal memory with task-specific token

Deep learning models generally display catastrophic forgetting when learning new data continuously. Many incremental learning approaches address this problem by reusing data from previous tasks while learning new tasks. However, the direct access to past data generates privacy and security concerns....

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Bibliographische Detailangaben

Hauptverfasser:	Choi, Young Jo, Yoo, Min Kyoon, Park, Yu Rang
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Learning
Online-Zugang:	Volltext bestellen
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