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Found 2 papers, 1 papers with code
Topology-Preserving Class-Incremental Learning
A well-known issue for class-incremental learning is the catastrophic forgetting phenomenon, where the network's recognition performance on old classes degrades severely when incrementally learning new classes.
Few-Shot Class-Incremental Learning
FSCIL requires CNN models to incrementally learn new classes from very few labelled samples, without forgetting the previously learned ones.
Ranked #8 on
Few-Shot Class-Incremental Learning
on CIFAR-100
(Average Accuracy metric)
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