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arXiv · 2004.08606

Feathers dataset for Fine-Grained Visual Categorization

Alina Belko·Konstantin Dobratulin·Andrey Kuznetsov
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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.

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Alina Belko, Konstantin Dobratulin, Andrey Kuznetsov. 2020-04-18. Feathers dataset for Fine-Grained Visual Categorization. https://arxiv.org/abs/2004.08606

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