This project aims to develop a standalone AI-based leather material inspection system for defect detection, classification, material utilization estimation, and optimized marker planning. The AI-driven defect detection system accurately identifies and classifies defects in all common types of leather materials used in finished products, achieving promising detection accuracy to automate the traditional human-based inspection process. Additionally, the system can be integrated with existing computerized marker planning systems to enhance the conventional marker planning process.

 

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Principal Investigator

Collaborating Investigator
Anne TOOMEY