Introduces adversarial contrastive training for cross-domain few-shot class-incremental audio classification, with encoder frozen after base session and classifier updated across sessions, outperforming SOTA on six dataset pairs.
Classification of urban sound using sequential convolutional neural network model and its visualisation,
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Cross Domain Few-Shot Class-Incremental Audio Classification Via Adversarial Contrastive Learning
Introduces adversarial contrastive training for cross-domain few-shot class-incremental audio classification, with encoder frozen after base session and classifier updated across sessions, outperforming SOTA on six dataset pairs.