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

Polish bird species recognition - Bird song analysis and classification with MFCC and CNNs. Trained on EfficientNets with final score 0.88 AUC. Women in Machine Learning & Data Science project.

Supervised Classification of bird species 🐦 in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data [ICVGIPW'18]

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!

Code for searching the www.xeno-canto.org bird sound database, and training a machine learning model to classify birds according to their sounds.

Explores jigsaw puzzles solvinig as pre-text task for fine grained classification for bird species identification (Implemented with pyTorch)

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

Southern African Bird Call Audio Identification Challenge

Bird Classifier developped in tensorflow using pre-trained model from Tensorflow Hub and running on Google Colab

Classifies a bird's species using a neural network in tensorflow..

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

Code used for my final project in Computer Vision at Texas State University, Spring 2019

BirdNET as a systemd service with other features.

Source code for BMBF InnoTruck demo of BirdNET.

Polish bird species recognition - Bird song analysis and classification. Women in Machine Learning & Data Science project.

Bird Species Classification using Inception-v3 Network

Applications to identify birds based on their appearance and taxonomy

Determine the 🐦 from its 🎵

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!

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…