Road Surface Damages

Research on damage detection of road surfaces has been an active area of research, but most studies have focused so far on the detection of the presence of damages. However, in real-world scenarios, road managers need to clearly understand the type of damage and its extent in order to take effective action in advance or to allocate the necessary resources. Moreover, currently there are few uniform and openly available road damage datasets, leading to a lack of a common benchmark for road damage detection. Such dataset could be used in a great variety of applications; herein, it is intended to serve as the acquisition component of a physical asset management tool which can aid governments agencies for planning purposes, or by infrastructure maintenance companies. described in https://github.com/sekilab/RoadDamageDetector/ and available here https://mycityreport.s3-ap-northeast-1.amazonaws.com/02_RoadDamageDataset/RoadDamageDataset.tar.gz), by incoporating more examples of potholes and longitudinal and alligator cracks

路面损伤检测的研究领域一直活跃于学术探讨，然而，迄今为止，多数研究集中于损伤存在的检测。然而，在现实场景中，道路管理者需明确了解损伤的类型及其严重程度，以便提前采取有效措施或分配必要的资源。此外，目前尚缺乏统一且公开可用的路面损伤数据集，导致路面损伤检测缺乏一个共同的基准。此类数据集可应用于众多领域；本数据集旨在作为物理资产管理工具的获取组件，辅助政府部门进行规划或基础设施维护公司进行维护工作。详情请见https://github.com/sekilab/RoadDamageDetector/，数据集可通过以下链接获取https://mycityreport.s3-ap-northeast-1.amazonaws.com/02_RoadDamageDataset/RoadDamageDataset.tar.gz），通过纳入更多坑洞以及纵向和鳄鱼裂纹的示例。