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TEMPL: A Resource-Efficient and Transparent Model-Free Framework for Pseudo-Label Generation in Material CT Scans
Ashiqur Rahman, Venkata Devesh Reddy Seethi, Austin Yunker +2
The scarcity of large annotated datasets limits deep learning (DL) segmentation in material CT analysis. DL-based pseudo-labeling can help, but it is often computationally expensiv…
Unsupervised Semantic Segmentation in Synchrotron Computed Tomography with Self-Correcting Pseudo Labels
Austin Yunker, Peter Kenesei, Hemant Sharma +3
X-ray computed tomography (CT) is a widely used imaging technique that provides detailed examinations into the internal structure of an object with synchrotron CT (SR-CT) enabling…
Effective Defect Detection Using Instance Segmentation for NDI
Ashiqur Rahman, Venkata Devesh Reddy Seethi, Austin Yunker +3
Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging…