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A list of useful resources in the bird sound (song and calls) recognition, such as datasets, papers, links to open source projects and competitions
Source code of the TUCMI submission to BirdCLEF2017
ResNet-34 Model trained from scratch to classify 450 different species of birds with 98.6% accuracy.
Classifies a bird's species using a neural network in tensorflow..
Free open information (CC0) about nature on planet earth
To set up the raspberry pi and cloud environment please visit the Nick branch; to set up the website please use the main branch.
Object detection dataset based on images from Macaulay Library for 29 bird species in the Pittsburgh area. The 29 species are a subset of the 400 species in the NABirds dataset. For each species, the dataset contains about 1000 labeled images.
A model inspired by inception v1 for classification of bird species