# B3 Data information course@tutorial — Data

来源：https://www.kaggle.com/competitions/b3-data-information-coursetutorial/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

引用元
https://www.kaggle.com/jessicali9530/stanford-dogs-dataset




Context
The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization. It was originally collected for fine-grain image categorization, a challenging problem as certain dog breeds have near identical features or differ in colour and age.

Content
Number of categories: 120
Number of images: 20,580
Annotations: Class labels, Bounding boxes
Acknowledgements
The original data source is found on http://vision.stanford.edu/aditya86/ImageNetDogs/ and contains additional information on the train/test splits and baseline results.

If you use this dataset in a publication, please cite the dataset on the following papers:

Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao and Li Fei-Fei. Novel dataset for Fine-Grained Image Categorization. First Workshop on Fine-Grained Visual Categorization (FGVC), IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [pdf] [poster] [BibTex]

Secondary:
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, ImageNet: A Large-Scale Hierarchical Image Database. IEEE Computer Vision and Pattern Recognition (CVPR), 2009. [pdf] [BibTex]

Banner Image from Hannah Lim on Unsplash