bird-species-classification

AKASH2907/bird_species_classification

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

wimlds-trojmiasto/birds

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.

davipatti/birdbrain

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

aniket03/self_supervised_bird_classification

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

UCSD-E4E/PyHa

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!

mcguirepr89/BirdNET-system

BirdNET as a systemd service with other features.

nripstein/What-Bird-is-That

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

Moddy2024/Bird-Classification

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

zahan97/Bird-Species-Classification

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

birdsiitmandi/birds_image_classification

Fine-grained species classification

kahst/BirdNET-Demo

Source code for BMBF InnoTruck demo of BirdNET.

LaurentVeyssier/Bird_Classifier_Tensorflow_Colab_Notebook

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

djl70/cv-bird-id

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

liuvince/mva-bird-recognition

MVA - Kaggle Challenge - Bird Image Recognition

NazarioR9/Fowl-Escapades-Solution

Southern African Bird Call Audio Identification Challenge

openavian/Bird-Sound-Recognition-with-Deep-Learning

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

Bobo100/BirdSoundRecognize

Bird Sound Recognize

kbrose/chorus

Determine the :bird: from its :musical_note:

dhuy228/bird_recognition

Experiment testing the feasibility of individual bird recognition from audio recordings

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.

HansSchouten/OpenNature

Free open information (CC0) about nature on planet earth

leilibrk/Image-Classification-Deep-Learning

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!

wimlds-trojmiasto/kosy

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

zulfiqarAlibalti/bird_classification

bird_classification web application

avocardio/resnet_vs_convnext

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

jiejin0327/2021-VRDL-HW1-Bird-Images-Classification

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.

Luckygyana/Bird-Species-Audio-Identification-Ensembling-and-1D-2D-Signals

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 Ornithology whose challenge is to identify which birds are calling in long recordings, given training data generated in meaningfully different contexts. This paper is structured in a way that it first gives details of the competition and the given data so that there is a clear understanding of the challenges posed by the train and test data. Also, we provide a detailed solution to the approaches we used for this challenge including data preparation, augmentations, model building, training procedure, and post-processing techniques.

AP-Y/birds-library

Applications to identify birds based on their appearance and taxonomy

kamrulhasanrony/Bird-Classification-Inception-v3

Bird Species Classification using Inception-v3 Network

khustochka/kjogvi

love124356/Bird-Classifier

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

NikhilK-84/remote-bird-species-detection-using-cnn-project

This project aims to detect bird species using a Convolutional Neural Network (CNN). The model was trained on six categories, including five bird species and one category for 'no bird detected'. The project includes resources for training the model and using it for detection and species recognition.

abelarduu/Bird-Photos-Website

Galeria online de fotos de aves, com design inspirado em cartões. Explore e aprecie a beleza das aves de forma intuitiva e organizada.