Automated lightweight networks for multi-material bridge crack segmentation

Key Points

• Segmentation accuracy improved by 25% using automated networks, indicating effectiveness in crack detection.
• Key metric shows a 25% increase in segmentation accuracy for bridge cracks during testing phases.
• Analysis utilized automated networks designed specifically for multi-material conditions in bridges.
• May enable more efficient and accurate inspections, enhancing structural safety in bridge engineering.