URDD: An open dataset for urban roadway disease detection and classification

Published: 2 December 2024| Version 1 | DOI: 10.17632/r7pnxpr2bb.1
Contributors:
Shuaiqi Liu, wenjing jiang, Yue Yu, Lei Ren, Chunbo Li, Qi Hu

Description

The urban road disease datasets we provide include DURDD and CURDD detection and classification, respectively. DURDD includes four main types of underground road diseases: cavity, detachment, water-rich, losseness. It also contains disease detection datasets in three base formats: COCO, Pascal VOC, and YOLO. In CURDD, the dataset is divided into two levels: level 0 and level 1, corresponding to the "Cls0" and "Cls1" catalogs, respectively. Level 1 includes cavity, detachment, water-rich, losseness, and background. Level 0 categories combine the four main disease types mentioned earlier into a single "diseases" category, with the other category being "background."

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Institutions

  • Hebei University

Categories

Earth Sciences, Computer Vision, Use of Computers in Earth Sciences

Funders

  • National Natural Science Foundation of China
    China
    Grant ID: 62172139
  • Funded by S&T Program of Hebei Province
    Grant ID: 246Z0104G
  • Science Foundation Science Research Project of Hebei Province
    Grant ID: CXY2024031
  • Hebei University Research and Innovation Team Support Project
    Grant ID: IT2023B05

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