Open Ecoacoustics make your own recogniser
Includes the requirements and practical steps required to make your own automated call recogniser using a convolution neural network.
The "Requirements" section includes demo data and requirements for the data you should include to develop your own recogniser as well as links to Anaconda & Raven Lite software.
The "Practical Steps" provides instructions to run the required Jupyter notebook to build a recogniser with CNN.
- Note additional AI methods will be available soon
Licence: Creative Commons Attribution 4.0
Contact: https://openecoacoustics.org/contact/
Keywords: Ecoacoustics, call recogniser, convolutional neural network
Additional information
Status: Active
Open Ecoacoustics make your own recogniser
https://openecoacoustics.org/resources/lessons/make-your-own-recognizer/
https://dresa.org.au/materials/open-ecoacoustics-make-your-own-recogniser
Includes the requirements and practical steps required to make your own automated call recogniser using a convolution neural network.
The "Requirements" section includes demo data and requirements for the data you should include to develop your own recogniser as well as links to Anaconda & Raven Lite software.
The "Practical Steps" provides instructions to run the required Jupyter notebook to build a recogniser with CNN.
* Note additional AI methods will be available soon
https://openecoacoustics.org/contact/
Dr Philip Eichinski
Dr Lance De Vine
Ecoacoustics, call recogniser, convolutional neural network
