论文标题
羽毛数据集用于细粒度的视觉分类
Feathers dataset for Fine-Grained Visual Categorization
论文作者
论文摘要
本文介绍了一种新型的数据集Featherv1，其中包含28,272张由595种鸟类分类的羽毛图像。它的创建是为了通过单个羽毛对鸟类进行分类学识别，该羽毛可以应用于业余和专业鸟类学。 Featherv1是第一个用于机器学习的公开鸟羽毛数据集，它可能会引起对细颗粒视觉识别域的新任务的兴趣。最新版本的数据集可以在https://github.com/feathers-dataset/feathersv1-dataset上下载。我们还提出了羽毛分类任务结果。我们选择了几个深度学习体系结构（基于Densenet），以比较提供的数据集。
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.
