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Anomaly detection of microstructural defects in continuous fiber reinforced composites.

, , , and . Computational Imaging, volume 9401 of SPIE Proceedings, page 94010A. IS&T/SPIE, (2015)

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Large-Scale Fiber Tracking Through Sparsely Sampled Image Sequences of Composite Materials., , , , and . IEEE Trans. Image Process., 25 (10): 4931-4942 (2016)Physics of MRF regularization for segmentation of materials microstructure images., , , , and . ICIP, page 4882-4886. IEEE, (2014)Anomaly detection of microstructural defects in continuous fiber reinforced composites., , , and . Computational Imaging, volume 9401 of SPIE Proceedings, page 94010A. IS&T/SPIE, (2015)Unsupervised Learning for Large-Scale Fiber Detection and Tracking in Microscopic Material Images., , , , , , and . CoRR, (2018)Quantitative Comparisons of Volumetric Datasets From Experiments and Computational Models., , , , , and . IEEE Access, (2023)Weakly supervised easy-to-hard learning for object detection in image sequences., , , , , , and . Neurocomputing, (2020)Groupwise Tracking of Crowded Similar-Appearance Targets from Low-Continuity Image Sequences., , , , , , , and . CVPR, page 952-960. IEEE Computer Society, (2016)Deep Learning for Object Detection in Materials-Science Images: A tutorial., , , , and . IEEE Signal Process. Mag., 39 (1): 78-88 (2022)On-the-Fly Performance Evaluation of Large-Scale Fiber Tracking., , , and . Computational Imaging, page 142-147. Society for Imaging Science and Technology, (2017)