Constructed an advanced deep learning model utilizing TensorFlow and CNN to precisely classify bird species from audio inputs. Leveraging Librosa for audio processing, the model is trained on extensive bird sound datasets to ensure robust performance. Integrated with Hugging Face, our application facilitates seamless uploading of bird sound samples

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!

bird_classification web application

Free open information (CC0) about nature on planet earth

Determine the 🐦 from its 🎵

Computer vision website which recognizes and provides information about birds in user-uploaded photos.

Using convolutional neural networks to build and train a bird species classifier on bird song data with corresponding species labels.

Explore deep learning-powered image classification with PyTorch. Achieved 98% accuracy on Natural Images and 95% on Birds Species using AlexNet and EfficientNet-B1. Dive into the code and results!

Bird Species Classification using Inception-v3 Network

This project is a bird classifier that uses the PyTorch framework and the ResNet50 model. It can recognize the species of birds in images based on their visual features. It supports 200 different categories of birds.

ResNet-34 Model trained from scratch to classify 450 different species of birds with 98.6% accuracy.

Selected Topics in Visual Recognition using Deep Learning, NYCU. CodaLab competition - Bird images classification

Bird Sound Recognize

New is not always better: a comparison of two image classification networks (ResNet-50 vs ConvNeXt).

Applications to identify birds based on their appearance and taxonomy

Signature Work @ DKU: Large Scale Bird Sound Recognition in China Region

BirdNET as a systemd service with other features.

There are about 10,000 different bird species in the world, and they play an important role in the natural world. They serve as good indicators of declining habitat quality and pollution. It is often easier to hear birds than it is to see them. Bird_CLEF 2021 - Birdcall Identification is a Kaggle competition organized by The Cornell Lab of Ornit…

MVA - Kaggle Challenge - Bird Image Recognition