Work

Yolov8 model weights to detect unknown underwater sounds

Year: 2026

Type: dataset

Abstract: Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings.Trained weights of model, in Python.Code to reproduce publication results, (re)train the models, or use the models for inference can be found on: GitHub - lifewatch/sound-segregation-and-categorization (https://github.com/lifewatch/sound-segregation-and-categorization).

Source: Flanders Marine Institute (Flanders Marine Institute)

DOI: 10.14284/808

Authors: Parcerisas, Clea, C., Schall, Elena, E., te Velde, Kees, K., Botteldooren, Dick, D., Devos, Paul, P., Debusschere, Elisabeth, E., Flanders Marine Institute (VLIZ), Belgium, WAVES - UGent, Ocean Acoustics Group - AWI, Germany, Institute of Biology - Universiteit Leiden, Netherlands

Institutions: Flanders Marine Institute, Ghent University, Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Leiden University

Language: English

Topic: Music and Audio Processing

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7167809641

Cites:

Cited by:

Related to: