activity
20172023
most citedLocal Fiber Orientation from X-ray Region-of-Interest Computed Tomography of large Fiber Reinforced Composite Components

45 citations · 68 across the 12 of their papers we have counts for

collaborators

12 papers

eess.IV2023

MorphFlow: Estimating Motion in In Situ Tests of Concrete

Tessa Nogatz, Claudia Redenbach, Katja Schladitz

We present a novel algorithm explicitly tailored to estimate motion from time series of 3D images of concrete. Such volumetric images are usually acquired by Computed Tomography an…

quant-ph2023★ 1 cited

Hybrid quantum transfer learning for crack image classification on NISQ hardware

Alexander Geng, Ali Moghiseh, Claudia Redenbach +1

Quantum computers possess the potential to process data using a remarkably reduced number of qubits compared to conventional bits, as per theoretical foundations. However, recent e…

cs.CV2023

Riesz feature representation: scale equivariant scattering network for classification tasks

Tin Barisin, Jesus Angulo, Katja Schladitz +1

Scattering networks yield powerful and robust hierarchical image descriptors which do not require lengthy training and which work well with very few training data. However, they re…

cs.CV2023★ 1 cited

Riesz networks: scale invariant neural networks in a single forward pass

Tin Barisin, Katja Schladitz, Claudia Redenbach

Scale invariance of an algorithm refers to its ability to treat objects equally independently of their size. For neural networks, scale invariance is typically achieved by data aug…

eess.IV2023★ 8 cited

Improved Anisotropic Gaussian Filters

Alex Keilmann, Michael Godehardt, Ali Moghiseh +2

Elongated anisotropic Gaussian filters are used for the orientation estimation of fibers. In cases where computed tomography images are noisy, roughly resolved, and of low contrast…

cs.CV2022

Assessing cloudiness in nonwovens

Michael Godehardt, Ali Moghiseh, Christine Oetjen +4

The homogeneity of filter media is important for material selection and quality control, along with the specific weight (nominal grammage) and the distribution of the local weight.…

quant-ph2022

A hybrid quantum image edge detector for the NISQ era

Alexander Geng, Ali Moghiseh, Claudia Redenbach +1

Edges are image locations where the gray value intensity changes suddenly. They are among the most important features to understand and segment an image. Edge detection is a standa…

cs.CV2022★ 3 cited

An unambiguous cloudiness index for nonwovens

Michael Godehardt, Ali Moghiseh, Christine Oetjen +2

Cloudiness or formation is a concept routinely used in industry to address deviations from homogeneity in nonwovens and papers. Measuring a cloudiness index based on image data is…

cs.CV2021

Methods for segmenting cracks in 3d images of concrete: A comparison based on semi-synthetic images

Tin Barisin, Christian Jung, Franziska Müsebeck +2

Concrete is the standard construction material for buildings, bridges, and roads. As safety plays a central role in the design, monitoring, and maintenance of such constructions, i…

quant-ph2021★ 1 cited

Improved FRQI on superconducting processors and its restrictions in the NISQ era

Alexander Geng, Ali Moghiseh, Claudia Redenbach +1

In image processing, the amount of data to be processed grows rapidly, in particular when imaging methods yield images of more than two dimensions or time series of images. Thus, e…

eess.IV2020★ 45 cited

Local Fiber Orientation from X-ray Region-of-Interest Computed Tomography of large Fiber Reinforced Composite Components

Thomas Baranowski, Dascha Dobrovolskij, Kilian Dremel +4

The local fiber orientation is a micro-structural feature crucial for the mechanical properties of parts made from fiber reinforced polymers. It can be determined from micro-comput…

physics.acc-ph2017★ 9 cited

Nb3Sn wire shape and cross sectional area inhomogeneity in Rutherford cables

U. Kelly, S. Richter, C. Redenbach +7

During Rutherford cable production the wires are plastically deformed and their initially round shape is distorted. Using X-ray absorption tomography we have determined the 3D shap…