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EAR MNHN (ear-team)

EAR MNHN

ear-team

Geek Repo

EcoAcoustics Research team at the Museum national d'histoire naturelle (MNHN) de Paris

Location:paris

Home Page:https://ear.cnrs.fr

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EAR MNHN's repositories

bambird

Unsupervised classification to improve the quality of a bird song recording dataset. https://doi.org/10.1016/j.ecoinf.2022.101952

Language:PythonLicense:BSD-3-ClauseStargazers:22Issues:1Issues:6

HAUPERT_MEE_2022

Physics‐based model to predict the acoustic detection distance of terrestrial autonomous recording units over the diel cycle and across seasons: Insights from an Alpine and a Neotropical forest. Haupert et. al. 2023, Methods in Ecology and Evolution.

Language:Jupyter NotebookStargazers:8Issues:1Issues:1

sound_source_localization

Repository companion to the paper : Lellouch & al. Sound source localization in a natural soundscape with autonomous recorder units based on a new time-difference-of-arrival algorithm

Language:Jupyter NotebookLicense:BSD-3-ClauseStargazers:6Issues:1Issues:0

darksound

Unsupervised meta-learning for improving clustering quality in unlabeled bird sound datasets

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:3Issues:0Issues:0

Grinfeder_Landscape_Ecology_2022

Soundscape dynamics of a cold protected forest: dominance of aircraft noise. https://link.springer.com/article/10.1007/s10980-021-01360-1

Language:Jupyter NotebookLicense:BSD-3-ClauseStargazers:2Issues:0Issues:0

scikit-maad

Open-source and modular toolbox for quantitative soundscape analysis in Python

Language:PythonLicense:BSD-3-ClauseStargazers:0Issues:0Issues:0

evascape

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haupert_acoustic_indices_2025

Codes for the paper

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