BirdNET-Analyzer and Bird-sound-classification-using-CNN

About BirdNET-Analyzer

birdnet-team/BirdNET-Analyzer

BirdNET analyzer for scientific audio data processing.

Leverages deep learning models trained on 6,512+ bird species to automatically detect and classify avian vocalizations in audio files or continuous streams. Provides both command-line and GUI interfaces designed for researchers without CS expertise, with support for batch processing large audio datasets and real-time analysis through Docker containerization. Integrates with Zenodo for model distribution and supports cross-platform deployment on Linux, Windows, and macOS via native installers or Python package management.

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.