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

Published: 2 December 2024| Version 1 | DOI: 10.17632/r7pnxpr2bb.1
Contributors:
, wenjing jiang,
, Lei Ren, Chunbo Li,

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

  • 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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