TITLE: Feathers dataset for Fine-Grained Visual Categorization 

ABSTRACT: This paper introduces a novel dataset FeatherV1, containing 28,272 images of
feathers categorized by 595 bird species. It was created to perform taxonomic
identification of bird species by a single feather, which can be applied in
amateur and professional ornithology. FeatherV1 is the first publicly available
bird's plumage dataset for machine learning, and it can raise interest for a
new task in fine-grained visual recognition domain. The latest version of the
dataset can be downloaded at
https://github.com/feathers-dataset/feathersv1-dataset. We also present
feathers classification task results. We selected several deep learning
architectures (DenseNet based) for categorical crossentropy values comparison
on the provided dataset.
This paper introduces a novel dataset FeatherV1, containing 28,272 images of
feathers categorized by 595 bird species. It was created to perform taxonomic
identification of bird species by a single feather, which can be applied in
amateur and professional ornithology. FeatherV1 is the first publicly available
bird's plumage dataset for machine learning, and it can raise interest for a
new task in fine-grained visual recognition domain. The latest version of the
dataset can be downloaded at
https://github.com/feathers-dataset/feathersv1-dataset. We also present
feathers classification task results. We selected several deep learning
architectures (DenseNet based) for categorical crossentropy values comparison
on the provided dataset.
Feathers dataset for Fine-Grained Visual Categorization
http://arxiv.org/abs/2004.08606v1