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Publisher
Technological University Dublin
Description
Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This work proposes an automatic patch detection system using an object detection technique. Results show that the object detection model can successfully detect patches inside LCMS images and suggest that the proposed approach could be integrated into the existing pavement inspection systems.
Publication Date
2023
Keywords
object detection, pavement inspection systems, road maintenance, deep learning
Disciplines
Computer Sciences
Conference
First Annual Teaching and Research Showcase 2023
DOI
https://doi.org/10.21427/5QFE-1973
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Hassan, S. I., O'Sullivan, D., Mckeever, S., Power, D., Mcgowan, R., & Feighan, K. (2023). Detecting Patches on Road Pavement Images Acquired with 3D Laser Sensors using Object Detection and Deep Learning. Technological University Dublin. DOI: 10.21427/5QFE-1973