Benjamin Cretois

This paper develops data-driven sampling strategies to improve bird detection models by selecting the most impactful samples for fine-tuning with limited annotations.

This study uses national-scale passive acoustic monitoring to track avian migration patterns and develop species distribution models for three passerine species.

The paper synthesizes passive acoustic monitoring data across ecosystems to assess global coverage and identify gaps in biodiversity monitoring.

This study uses deep learning to analyze acoustic data and shows snowmobile noise reduces bird vocalizations in winter and pre-breeding seasons, with some recovery after noise events.

This paper develops ecoVAD, a VAD model for eco-acoustic data that outperforms existing models and enables privacy protection and human disturbance quantification.