Computational Sustainability
Machine Learning for Passive Acoustic Wildlife Monitoring: Methods for Semi-Automated Population and Species Assessment
Passive acoustic monitoring (PAM) has become a powerful tool for studying wildlife by continuously recording environmental soundscapes. However, analysing large acoustic datasets remains highly time-consuming, as recordings are often annotated manually by domain experts. In this work, we investigate how machine learning can support scalable biodiversity monitoring by enabling efficient Read more
