A pre-failure narrow concrete cracks dataset for engineering structures damage classification and segmentation.

ABSTRACT: Monitoring of structures' condition plays a fundamental role in providing safety for users and extending the structures' lifespan. The monitoring is conducted through on-site inspections by engineers thus this process is time-consuming, labor-intensive and prone to subjective engineering opinions. Detecting damage using machine learning algorithms on images can support engineers' work, especially for early damages which are difficult to see with the human eye. This article is focused on the concrete crack detection problem in engineering structural elements. Despite the availability of several concrete crack detection datasets, no dataset allows semantic segmentation of cracks narrower than 0.3 mm (the crack width limit for typical engineering structures elements and environmental conditio

SUBMITTER: Tomaszkiewicz K 

PROVIDER: S-EPMC10739794 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature