S-Space: Seoul National University
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A quantitative analysis of weakly and strongly labeled learning for CNN-transformer-based sound event detection of marine mammal vocalizations
Passive Acoustic Monitoring (PAM) data are inherently challenging to analyze because of high ambient noise levels and the large volume of long-term recordings. These difficulties are further amplified in marine mammal monitoring, where acoustic characteristics vary substantially across species and r
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