Instruction-tuned vision-language model PaveGPT, trained on a large unified pavement dataset, achieves substantial gains over general models in comprehensive, standard-compliant pavement condition assessment.
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Fine-tuned YOLOv11 achieves F1-score of 0.84 on highway crack detection from open data, yielding a new Swiss RHCD index with weak correlations to temperature and traffic data.
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Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment
Instruction-tuned vision-language model PaveGPT, trained on a large unified pavement dataset, achieves substantial gains over general models in comprehensive, standard-compliant pavement condition assessment.
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Automated Road Crack Localization for Spatially Guided Highway Maintenance
Fine-tuned YOLOv11 achieves F1-score of 0.84 on highway crack detection from open data, yielding a new Swiss RHCD index with weak correlations to temperature and traffic data.