Research output per year
Research output per year
Search results
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2024
Unsupervised Segmentation of Industrial X-ray Computed Tomography Data with the Segment Anything Model
Weinberger, P., Schwarz, L., Fröhler, B., Gall, A., Heim, A., Yosifov, M., Bodenhofer, U., Kastner, J. & Senck, S., 1 Jan 2024, (Submitted) In: Journal of Nondestructive Evaluation. 1 p.Research output: Contribution to journal › Article › peer-review
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2023
Application of a modified 3D U-Net convolutional neural network architecture for the inspection of aerospace components
Yosifov, M., Weinberger, P., Fröhler, B., Plank, B., Kastner, J. & Heinzl, C., 2023, In: e-Journal of Nondestructive Testing . 28, 3, 6 p.Research output: Contribution to journal › Conference article
Open Access -
Defect detectability analysis via probability of defect detection between traditional and deep learning methods in numerical simulations
Yosifov, M., Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J. & Heinzl, C., 2023, In: e-Journal of Nondestructive Testing . 28, 3, 10 p.Research output: Contribution to journal › Conference article
Open Access -
Segmentation of Pores in Carbon Fiber Reinforced Polymers Using the U-Net Convolutional Neural Network
Yosifov, M., Weinberger, P., Plank, B., Fröhler, B., Höglinger, M., Kastner, J. & Heinzl, C., 11 Oct 2023, In: Acta Polytechnica CTU Proceedings. 2023, 42, p. 87-93 7 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Usage of 3D U-net Convolutional Neural Network for the inspection of aerospace components
Yosifov, M., Weinberger, P., Fröhler, B., Plank, B., Kastner, J. & Heinzl, C., Mar 2023, In: e-Journal of Nondestructive Testing. 28, 3Research output: Contribution to journal › Article
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2022
Probability of Detection applied to X-ray inspection using numerical simulations
Yosifov, M., Reiter, M., Heupl, S., Gusenbauer, C., Fröhler, B., Fernández-Gutiérrez, R., De Beenhouwer, J., Sijbers, J., Kastner, J. & Heinzl, C., 2022, In: Nondestructive Testing and Evaluation. 37, 5, p. 536-551 16 p.Research output: Contribution to journal › Article › peer-review
Open Access12 Citations (Scopus) -
The long journey to the training of a deep neural network for segmenting pores and fibers
Yosifov, M., Weinberger, P., Fröhler, B., Kastner, J. & Heinzl, C., 2022, (Accepted/In press) Proceedings of the Industrial Computed Tomography Conference (iCT) 2022.Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review