Showing cs.SDShow all
3 papers · 1 filter
cs.SD2026
Determinantal point process sampling for bioacoustic active learning
Hugo Magaldi, Gabriel Dubus
Eco-acoustic monitoring generates vast volumes of audio data, making active learning a promising approach for reducing annotation effort while efficiently training reliable biodive…
cs.SD2026
Adaptive Diversity-Uncertainty Active Learning with Redundancy Control for Bioacoustic Event Classification
Gabriel Dubus, Hugo Magaldi, Anatole Gros-Martial
Active learning is a promising framework for reducing annotation costs in large-scale bioacoustic monitoring, where expert labeling is expensive and data distributions are highly h…
cs.SD2026
DeepForestSound: a multi-species automatic detector for passive acoustic monitoring in African tropical forests, a case study in Kibale National Park
Gabriel Dubus, Théau d'Audiffret, Claire Auger +10
Passive Acoustic Monitoring (PAM) is widely used for biodiversity assessment. Its application in African tropical forests is limited by scarce annotated data, reducing the performa…