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- BirdNET Sound ID – The easiest way to identify birds by sound.
Learn how to identify birds by sound with the Cornell Lab of Ornithology’s free BirdNET mobile app and website Advances in machine learning are making it easier to identify birds by their sounds Q A with BirdNET developer Stefan Kahl
- Species List – BirdNET Sound ID - Cornell University
This project is supported by Jake Holshuh (Cornell class of ’69) and The Arthur Vining Davis Foundations Our work in the K Lisa Yang Center for Conservation Bioacoustics is made possible by the generosity of K Lisa Yang to advance innovative conservation technologies to inspire and inform the conservation of wildlife and habitats
- About Us – BirdNET Sound ID - Cornell University
BirdNET Sound ID Menu Home; Live Stream Demo; Upload Recording; Android App; iOS App; Submissions Map; About Us The demos and apps on this page are proof-of-concept prototypes and by no means final products We would like you to join us and explore the possibilities of machine learning for bird song identification with these applications If
- BirdNET - Cornell University
BirdNET K Lisa Yang Center for Conservation Bioacoustics No data available Please upload an audio file (maximum duration of 10 minutes) containing bird sounds Help us to improve BirdNET! Please take a moment to fill out our survey Contact: ccb-birdnet@cornell edu
- BirdNET LiveMap - Cornell University
This map shows anonymized BirdNET observations Click on the markers to see more details Hide
- Bird Sound Samples – BirdNET Sound ID - Cornell University
Bird Sound Samples The following samples of bird sounds are intended to illustrate the tremendous variety of bird vocalizations as part of my dissertation “Identifying Birds by Sound: Large-scale Acoustic Event Classification for Avian Activity Monitoring” The sample IDs listed below correspond with samples marked in the text of my thesis
- Collaborate – BirdNET Sound ID - Cornell University
Are you currently researching a topic where BirdNET could be helpful, or do you have an idea for a research project? Let us know! You would like to support us in the area of software and app development? Please contact us We are open to your ideas and would love to talk with you Send us an email: ccb-birdnet@cornell edu
- Privacy Policy – BirdNET Sound ID - Cornell University
BirdNET is an artificial neural network that identifies bird species by sound Our servers process small audio snippets recorded with the BirdNET app to detect and recognize bird sounds We store all submitted recordings on our servers
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