bioacoustic monitoring

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papersTODAY 04:00 UTC

Deep learning segmentation framework detects fin whale calls in ocean-bottom seismic data

Researchers present a semantic segmentation deep learning framework for large-scale bioacoustic detection, applied to fin whale calls recorded by ocean-bottom seismometers. The approach repurposes seismic instruments, originally deployed for geophysics, as a broad-area passive acoustic monitoring network. This could expand monitoring of baleen whales over long time spans and wide ocean regions.

bioacoustics/deep-learning/marine-monitoring/segmentation

papersTODAY 04:00 UTC

arXiv paper proposes active learning framework for bioacoustic monitoring

A new preprint introduces BioDCASE, an active learning approach aimed at reducing the labeling burden in passive acoustic monitoring for ecology. The work targets the high cost of annotating large audio datasets by selecting which recordings are most worth labeling. It is published on arXiv under the cs.LG category.

active-learning/bioacoustics/research/labeling