R4-B.4: Integrated Reconstruction/Recognition
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چکیده
In CT-based security screening, a challenging problem is to correctly identify and label objects in a scene from X-ray projection data. The presence of artifacts in the reconstructed image confounds traditional segmentation and labeling methods. In this work, we focus on integrating machine learning, physical modeling and Bayesian inference in a framework for direct material identifi cation and labeling. Such an approach can mitigate image artifacts, reduce the number of corner cases and minimize false alarms.
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