A parameter-efficient dual-encoder model with differentiable Choquet integral fusion improves underwater acoustic classification accuracy over single-encoder baselines on DeepShip and ShipsEar datasets.
CNN architectures for large-scale audio clas- sification,
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CoughPhase-CLR uses cough physiological phases to build contrastive positive pairs, outperforming random cropping on downstream tasks including COVID-19 detection and COPD classification.
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Parameter-efficient Dual-encoder Architecture with Differentiable Choquet Integral Fusion for Underwater Acoustic Classification
A parameter-efficient dual-encoder model with differentiable Choquet integral fusion improves underwater acoustic classification accuracy over single-encoder baselines on DeepShip and ShipsEar datasets.
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CoughPhase-CLR: Designing an acoustics-informed foundation model for coughing sound classification
CoughPhase-CLR uses cough physiological phases to build contrastive positive pairs, outperforming random cropping on downstream tasks including COVID-19 detection and COPD classification.