Defect detection using YOLOv8 for determining the condition of asphalt pavements
Abstract
This study aimed to evaluate the capacity of the YOLOv8 algorithm to detect potholes, patches, and cracks. To achieve this, a section of a highway was recorded, manually evaluated in the field, and compared with a semi-automatic evaluation based on video processing by the model. The model yielded different results from those obtained through field assessment. Although only a portion of the Maintenance Condition Index is used in the assessment, this marks the first use of an index integrated with YOLOv8. Thus, it is concluded that the model requires further improvements to become viable for definitive application.
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References
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Copyright (c) 2025 Souza, A.M., Oliveira, C.E., Decker, P.H.B., Amorim, G.E.R., Correa, A.L.S.C, Fontenele, H.B.
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