gopiashokan/Bird-Sound-Classification-using-Deep-Learning
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.
This tool helps ecologists and conservationists identify bird species from their audio recordings. You input audio files of bird vocalizations, and it tells you which of 114 bird species are present. This helps researchers quickly analyze fieldwork data and monitor avian populations.
No commits in the last 6 months.
Use this if you need to identify bird species from audio recordings for wildlife research, environmental monitoring, or conservation efforts.
Not ideal if you need to classify sounds other than bird vocalizations or require identification beyond the 114 species currently supported.
Stars
21
Forks
7
Language
Jupyter Notebook
License
—
Category
Last pushed
Jul 18, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/gopiashokan/Bird-Sound-Classification-using-Deep-Learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
birdnet-team/BirdNET-Analyzer
BirdNET analyzer for scientific audio data processing.
tphakala/birdnet-go
Realtime BirdNET soundscape analyzer
birdnet-team/birdnet
A Python library for identifying bird species by their sounds.
DrCoffey/DeepSqueak
DeepSqueak v3: Using Machine Vision to Accelerate Bioacoustics Research
ear-team/bambird
Unsupervised classification to improve the quality of a bird song recording dataset....