detectors/ssb_easy-ood

Name: detectors/ssb_easy-ood
Creator: detectors
Published: 2024-03-04T19:09:38+08:00

Hugging Face2023-10-30 更新2024-03-04 收录

图像分类

异常检测

数据链接：

https://hf-mirror.com/datasets/detectors/ssb_easy-ood 数据链接链接失效反馈

官方服务：

资源简介：

--- license: unknown size_categories: n<1K task_categories: - image-classification pretty_name: SSB (easy) configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: image dtype: image splits: - name: train num_bytes: 41921235.0 num_examples: 151 download_size: 0 dataset_size: 41921235.0 --- # Dataset Card for SSB (easy) for OOD Detection  ## Dataset Details ### Dataset Description  - **Original Dataset Authors**: Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman - **OOD Split Authors:** Julian Bitterwolf, Maximilian Müller, Matthias Hein - **Shared by:** Eduardo Dadalto - **License:** unknown ### Dataset Sources  - **Original Dataset Paper:** http://arxiv.org/abs/2110.06207v2 - **First OOD Application Paper:** http://arxiv.org/abs/2306.00826v1 ### Direct Use  This dataset is intended to be used as an ouf-of-distribution dataset for image classification benchmarks. ### Out-of-Scope Use  This dataset is not annotated. ### Curation Rationale  The goal in curating and sharing this dataset to the HuggingFace Hub is to accelerate research and promote reproducibility in generalized Out-of-Distribution (OOD) detection. Check the python library [detectors](https://github.com/edadaltocg/detectors) if you are interested in OOD detection. ### Personal and Sensitive Information  Please check original paper for details on the dataset. ### Bias, Risks, and Limitations  Please check original paper for details on the dataset. ## Citation  **BibTeX:** ```bibtex @software{detectors2023, author = {Eduardo Dadalto}, title = {Detectors: a Python Library for Generalized Out-Of-Distribution Detection}, url = {https://github.com/edadaltocg/detectors}, doi = {https://doi.org/10.5281/zenodo.7883596}, month = {5}, year = {2023} } @article{2306.00826v1, author = {Julian Bitterwolf and Maximilian Müller and Matthias Hein}, title = {In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation}, year = {2023}, month = {6}, note = {ICML 2023. Datasets, code and evaluation data at https://github.com/j-cb/NINCO}, archiveprefix = {arXiv}, url = {http://arxiv.org/abs/2306.00826v1} } ``` ## Dataset Card Authors Eduardo Dadalto ## Dataset Card Contact https://huggingface.co/edadaltocg

license: 未知 size_categories: 样本数少于1000 task_categories: - 图像分类（image-classification） pretty_name: SSB（简易版） configs: - config_name: 默认 data_files: - split: 训练集 path: data/train-* dataset_info: features: - name: 图像（image） dtype: 图像（image） splits: - name: 训练集 num_bytes: 41921235.0 num_examples: 151 download_size: 0 dataset_size: 41921235.0 # 适用于分布外（Out-of-Distribution, OOD）检测的SSB（简易版）数据集卡片 ## 数据集详情 ### 数据集描述 - **原始数据集作者**: 萨加尔·瓦泽（Sagar Vaze）、韩凯（Kai Han）、安德里亚·韦达迪（Andrea Vedaldi）、安德鲁·齐斯曼（Andrew Zisserman） - **分布外拆分集作者**: 朱利安·比特沃夫（Julian Bitterwolf）、马克西米利安·缪勒（Maximilian Müller）、马蒂亚斯·海因（Matthias Hein） - **共享者**: 爱德华多·达达尔托（Eduardo Dadalto） - **许可证**: 未知 ### 数据集来源  - **原始数据集论文**: http://arxiv.org/abs/2110.06207v2 - **首个分布外检测应用论文**: http://arxiv.org/abs/2306.00826v1 ### 直接使用场景  本数据集旨在作为图像分类基准测试的分布外检测数据集。 ### 超出适用范围的使用场景  本数据集未进行标注。 ### 数据集构建初衷  本数据集面向HuggingFace Hub进行整理与共享，旨在加速通用分布外（Out-of-Distribution, OOD）检测领域的研究，并提升相关研究的可复现性。若您对分布外检测研究感兴趣，可查阅Python库[detectors](https://github.com/edadaltocg/detectors)。 ### 个人与敏感信息说明  有关本数据集的详细信息，请查阅原始论文。 ### 偏差、风险与局限性  有关本数据集的偏差、风险及局限性细节，请查阅原始论文。 ## 引用信息  **BibTeX:** bibtex @software{detectors2023, author = {"Eduardo Dadalto"}, title = {"Detectors: a Python Library for Generalized Out-Of-Distribution Detection"}, url = {"https://github.com/edadaltocg/detectors"}, doi = {"https://doi.org/10.5281/zenodo.7883596"}, month = {5}, year = {2023} } @article{2306.00826v1, author = {"Julian Bitterwolf and Maximilian Müller and Matthias Hein"}, title = {"In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation"}, year = {2023}, month = {6}, note = {"ICML 2023. Datasets, code and evaluation data at https://github.com/j-cb/NINCO"}, archiveprefix = {arXiv}, url = {"http://arxiv.org/abs/2306.00826v1"} } ## 数据集卡片作者爱德华多·达达尔托（Eduardo Dadalto） ## 数据集卡片联系方式 https://huggingface.co/edadaltocg

提供机构：

detectors

原始信息汇总

数据集卡片 SSB (easy)

数据集详情

数据集描述

原始数据集作者: Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman
OOD 分割作者: Julian Bitterwolf, Maximilian Müller, Matthias Hein
共享者: Eduardo Dadalto
许可证: unknown

数据集来源

原始数据集论文: http://arxiv.org/abs/2110.06207v2
首次OOD应用论文: http://arxiv.org/abs/2306.00826v1

直接使用

该数据集旨在用作图像分类基准的分布外数据集。

超出范围的使用

该数据集未标注。

数据集创建动机

创建和共享此数据集的目标是加速研究并促进广义分布外检测的可重复性。

个人和敏感信息

请查阅原始论文以获取数据集的详细信息。

偏差、风险和限制

请查阅原始论文以获取数据集的详细信息。

引用

BibTeX:

bibtex @software{detectors2023, author = {Eduardo Dadalto}, title = {Detectors: a Python Library for Generalized Out-Of-Distribution Detection}, url = {https://github.com/edadaltocg/detectors}, doi = {https://doi.org/10.5281/zenodo.7883596}, month = {5}, year = {2023} }

@article{2306.00826v1, author = {Julian Bitterwolf and Maximilian Müller and Matthias Hein}, title = {In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation}, year = {2023}, month = {6}, note = {ICML 2023. Datasets, code and evaluation data at https://github.com/j-cb/NINCO}, archiveprefix = {arXiv}, url = {http://arxiv.org/abs/2306.00826v1} }