Autonomous Defect Learning and Detection Engine for inspection system & on-board remote-controlled systems
Implementation Time:
9 months
Solution Provider: AI Singapore
How can industries automate and improve the efficiency and accuracy in the asset visual inspection process using computer vision to achieve high precision and accuracy while saving costs and time?
The computer vision models were deployed on the DeepDIVE platform for enabling pre-filtering of visual data for human expert verification and certification.
- Trained and deployed several object detection models to detect and annotate 3 types of common defects in Oil & Gas structures ( corrosion/rust, crack and deformation)
- The models are exposed via an Application Programming Interface (API) that can be consumed by services in Oceans.AI
- Predictions from the models can be fine-tuned by human experts, and this feedback can then be used to retrain the models
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Solution Diagram
Implementation Time
9 months
Use Case Brochure
