Bearing Condition State Classification Dataset

This is a dataset of structural bridge bearings. The
bearings have been annotated using the American Association of State Highway
and Transportation Officials (AASHTO) bridge inspection condition state
guidelines and Bridge Inspector's Reference Manual (BIRM). The authors have
included annotation guidelines and provided examples and explanation for
bearings and their respective condition state assessment. There are a total of
947 images of bearings included in the dataset. The image size is 300x300. The
bearing images were obtained from the COCO-Bridge-2021+ (Bianchi) dataset for
structural detail detection. The data was split 10% testing, 90% training. After
training with the EfficientNet B3 model (DOI: 10.7294/16628698), we were able
to obtain an F1 score of 86.4%. More details of the training, the results, the
dataset, and the code may be referenced in the journal article. The GitHub
repository information may be found in the journal article. If you are using the dataset in your work, please include both the journal article and the dataset citation.

本数据集收录了结构桥梁支座的图像。这些支座已根据美国州际公路与运输官员协会（AASHTO）桥梁检查状况指导方针以及《桥梁检查员参考手册》（BIRM）进行标注。作者们提供了标注指南，并对支座及其相应状况评估进行了实例说明与解释。数据集中包含共计947张支座图像，图像尺寸为300x300像素。支座图像来源于COCO-Bridge-2021+（Bianchi）数据集，旨在用于结构细节检测。数据集按照10%用于测试，90%用于训练的比例进行划分。在EfficientNet B3模型（DOI: 10.7294/16628698）的训练后，我们成功实现了86.4%的F1分数。关于训练细节、结果、数据集及代码的更多详情，可参考相关期刊文章。期刊文章中可找到GitHub仓库信息。若您在使用本数据集进行工作时，请务必引用期刊文章和数据集引用。