AI-Powered Real-Time Structural Crack & Spalling Depth Estimator
Monocular depth estimation and Mask R-CNN network measuring bridge and pillar concrete fracture width down to sub-millimeter precision.
Project Overview
Mounted on handheld inspection devices or inspection drones. Combines monocular depth estimation models with Mask R-CNN crack segmentation to accurately calculate crack length, surface aperture width (mm), and surface spalling volume on concrete infrastructure.
Mounted on handheld inspection devices or inspection drones. Combines monocular depth estimation models with Mask R-CNN crack segmentation to accurately calculate crack length, surface aperture width (mm), and surface spalling volume on concrete infrastructure.
Monocular depth estimation and Mask R-CNN network measuring bridge and pillar concrete fracture width down to sub-millimeter precision.
Core Project Objectives
Capture continuous analog/digital sensor readings with robust noise filtering and hardware calibration.