BirdNET-Analyzer and Bird-sound-classification-using-CNN
The deep learning model B is a competitor to the robust analyzer A, as both aim to classify bird species from audio, with B representing a user-developed solution and A being a more established, general-purpose tool.
About BirdNET-Analyzer
birdnet-team/BirdNET-Analyzer
BirdNET analyzer for scientific audio data processing.
This tool helps scientists and conservationists analyze large collections of recorded audio to identify bird species. You input audio files from your fieldwork, and it tells you which bird species are present in the recordings. It's designed for researchers, biologists, and ecologists who monitor bird populations or study avian behavior.
About Bird-sound-classification-using-CNN
DhanushS-11/Bird-sound-classification-using-CNN
Engineered a robust deep learning model using Convolutional Neural Networks and TensorFlow to classify 114 bird species based on audio recordings. Model achieved an impressive accuracy of 78.75%, providing valuable insights for conservationists and ecologists in the wildlife & ecological research sectors.
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