DAGM2007

这是一个用于在纹理表面上进行缺陷检测的合成数据集。它最初是为 2007 年 DAGM 研讨会（Deutsche Arbeitsgemeinschaft für Mustererkennung eV，国际模式识别协会的德国分会）的竞赛而创建的。比赛与 GNSS（欧洲神经网络学会德国分会）共同主办。比赛结束后，该数据集已在多个项目和研究论文中用作测试数据集。它可从海德堡大学网站（Heidelberg Collaboratory for Image Processing）公开获得。数据是人工生成的，但类似于现实世界的问题。十个数据集中的前六个，称为开发数据集，应该用于算法开发。其余四个数据集，称为竞争数据集，可用于评估性能。研究人员应考虑在开发完成之前不使用或分析竞赛数据集作为荣誉守则。

This is a synthetic dataset designed for defect detection on textured surfaces. It was initially developed for the competition held at the 2007 DAGM Symposium (Deutsche Arbeitsgemeinschaft für Mustererkennung eV, the German chapter of the International Association for Pattern Recognition). The competition was co-hosted with GNSS, the German Chapter of the European Neural Network Society. Following the conclusion of the competition, this dataset has been utilized as a test dataset across numerous projects and peer-reviewed research papers. It is publicly accessible through the website of the Heidelberg Collaboratory for Image Processing at Heidelberg University. The data is artificially generated yet closely resembles real-world defect detection scenarios. Of the ten total datasets, the first six, designated as the development datasets, are intended for algorithm development. The remaining four datasets, termed the competition datasets, may be used for performance evaluation. Researchers are encouraged to adhere to the honor code by refraining from using or analyzing the competition datasets prior to finalizing their algorithm development.