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bird-species-classification

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A repo designed to convert audio-based "weak" labels to "strong" intraclip labels. Provides a pipeline to compare automated moment-to-moment labels to human labels. Methods range from DSP based foreground-background separation, cross-correlation based template matching, as well as bird presence sound event detection deep learning models!

  • Updated Nov 22, 2024
  • Jupyter Notebook

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 93.4%, providing valuable insights for conservationists and ecologists in the wildlife & ecological research sectors.

  • Updated Jul 18, 2024
  • Jupyter Notebook

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