Defect data for industrial inspection.
Defect detection on industrial and subsea assets means telling true defects from staining and artifacts, at high volume.
defects · subsea · at volume
The problem
The skill is knowing what isn't a defect.
Detecting coating breakdown (corrosion and paint peel-off) on subsea and marine structures requires distinguishing true defects from staining, artifacts and masked regions.
At inspection volumes, that calibration is exactly where crowd labeling falls apart.
How io-ai helps.
Trained experts, an SOP-driven QA pipeline, and rejection-reason metadata on every task, held to over 98% accuracy.
Coating-breakdown segmentation
Tight polygons for corrosion, lifting and stripped areas.
Artifact-vs-defect calibration
Staining, lens artifacts and masks correctly excluded.
Multi-class item annotation
Tight boxes with occlusion rules, exported to YOLO v5.
Scaled delivery
Tens of thousands of tasks per workstream.
Modalities & techniques
image
polygon (V7 Darwin)
YOLO v5
Proven work.
A real industrial inspection engagement, with a hard number.
Industrial Inspection · Segmentation
>98%
accuracy on coating-breakdown segmentation at scale
Subsea coating-breakdown defect annotation.
Abyss Solutions
Read the case study
Let's talk
Tell us what you're building.
Send us your data challenge and we'll scope a pilot, usually within a couple of working days.