Feathers dataset for Fine-Grained Visual Categorization

• URL: http://arxiv.org/abs/2004.08606v1
• Date: Sat, 18 Apr 2020 12:40:43 GMT
• Title: Feathers dataset for Fine-Grained Visual Categorization
• Authors: Alina Belko, Konstantin Dobratulin and Andrey Kuznetsov
• Abstract summary: FeatherV1 is the first publicly available bird's plumage dataset for machine learning. It can raise interest for a new task in fine-grained visual recognition domain.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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