no code implementations • 2 Apr 2017 • Claudius Zelenka, Reinhard Koch
In most coherent imaging systems, especially in astronomy, the wavefront deformation is known.
1 code implementation • 3 Dec 2018 • Stefan Reinhold. Timo Damm, Lukas Huber, Reimer Andresen, Reinhard Barkmann, Claus-C. Glüer, Reinhard Koch
Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring.
1 code implementation • 30 Jul 2019 • Lars Schmarje, Claudius Zelenka, Ulf Geisen, Claus-C. Glüer, Reinhard Koch
Furthermore, we compare a variety of 2D and 3D methods such as classical approaches like Fourier analysis with state-of-the-art deep neural networks for the classification of local fiber orientations.
no code implementations • 20 Feb 2020 • Lars Schmarje, Monty Santarossa, Simon-Martin Schröder, Reinhard Koch
In this survey, we provide an overview of often used ideas and methods in image classification with fewer labels.
no code implementations • 19 Mar 2020 • Yuan Gao, Robert Bregovic, Reinhard Koch, Atanas Gotchev
Specifically, for an input sparsely-sampled EPI, DRST employs a deep fully Convolutional Neural Network (CNN) to predict the residuals of the shearlet coefficients in shearlet domain in order to reconstruct a densely-sampled EPI in image domain.
1 code implementation • 4 May 2020 • Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator and allows experts to adapt the granularity of their sorting scheme to the structure in the data.
no code implementations • 21 May 2020 • Johannes Brünger, Maria Gentz, Imke Traulsen, Reinhard Koch
In recent years, methods based on deep learning have been introduced and have shown pleasingly good results.
no code implementations • 18 Sep 2020 • Stefan Reinhold, Timo Damm, Sebastian Büsse, Stanislav N. Gorb, Claus-C. Glüer, Reinhard Koch
Quantitative computed tomography (QCT) permits the selective analysis of cortical bone, however the low spatial resolution of clinical QCT leads to an overestimation of the thickness of cortical bone (Ct. Th) and bone strength.
1 code implementation • 3 Dec 2020 • Lars Schmarje, Johannes Brünger, Monty Santarossa, Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
We propose a novel loss to improve the overclustering capability of our framework and show on the common image classification dataset STL-10 that it is faster and has better overclustering performance than previous work.
1 code implementation • 30 Jun 2021 • Lars Schmarje, Monty Santarossa, Simon-Martin Schröder, Claudius Zelenka, Rainer Kiko, Jenny Stracke, Nina Volkmann, Reinhard Koch
In our data-centric approach, we propose a method to relabel such ambiguous labels instead of implementing the handling of this issue in a neural network.
no code implementations • 7 Jul 2021 • Monty Santarossa, Lukas Schneider, Claudius Zelenka, Lars Schmarje, Reinhard Koch, Uwe Franke
Stixels have been successfully applied to a wide range of vision tasks in autonomous driving, recently including instance segmentation.
no code implementations • 29 Sep 2021 • Lars Schmarje, Monty Santarossa, Simon-Martin Schröder, Claudius Zelenka, Rainer Kiko, Jenny Stracke, Nina Volkmann, Reinhard Koch
Semi-Supervised Learning (SSL) can decrease the required amount of labeled image data and thus the cost for deep learning.
1 code implementation • 13 Oct 2021 • Lars Schmarje, Johannes Brünger, Monty Santarossa, Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
We propose a novel loss to improve the overclustering capability of our framework and show the benefit of overclustering for fuzzy labels.
no code implementations • 13 Oct 2021 • Lars Schmarje, Reinhard Koch
We envision the incorporation of fuzzy labels into Semi-Supervised Learning and give a proof-of-concept of the potential lower costs and higher consistency in the complete development cycle.
1 code implementation • 9 Mar 2022 • Tim Michels, Arne Petersen, Reinhard Koch
Camera calibration methods usually consist of capturing images of known calibration patterns and using the detected correspondences to optimize the parameters of the assumed camera model.
2 code implementations • 9 Mar 2022 • Tim Michels, Arne Petersen, Luca Palmieri, Reinhard Koch
Plenoptic cameras enable the capturing of spatial as well as angular color information which can be used for various applications among which are image refocusing and depth calculations.
3 code implementations • 9 Mar 2022 • Tim Michels, Reinhard Koch
The design of a plenoptic camera requires the combination of two dissimilar optical systems, namely a main lens and an array of microlenses.
no code implementations • 13 Jul 2022 • Vasco Grossmann, Lars Schmarje, Reinhard Koch
High-quality data is a key aspect of modern machine learning.
1 code implementation • 13 Jul 2022 • Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Sabine Dippel, Rainer Kiko, Mariusz Oszust, Matti Pastell, Jenny Stracke, Anna Valros, Nina Volkmann, Reinhard Koch
We propose a data-centric image classification benchmark with ten real-world datasets and multiple annotations per image to allow researchers to investigate and quantify the impact of such data quality issues.
no code implementations • 22 Jul 2022 • Lars Schmarje, Stefan Reinhold, Timo Damm, Eric Orwoll, Claus-C. Glüer, Reinhard Koch
We show that FORM can correctly predict the 10-year hip fracture risk with a validation AUC of 81. 44 +- 3. 11% / 81. 04 +- 5. 54% (mean +- STD) including additional information like age, BMI, fall history and health background across a 5-fold cross validation on the X-ray and CT cohort, respectively.
no code implementations • 28 Jul 2022 • Claudius Zelenka, Marius Kamp, Kolja Strohm, Akram Kadoura, Jacob Johny, Reinhard Koch, Lorenz Kienle
Accurately measuring the size, morphology, and structure of nanoparticles is very important, because they are strongly dependent on their properties for many applications.
1 code implementation • 22 May 2023 • Lars Schmarje, Vasco Grossmann, Tim Michels, Jakob Nazarenus, Monty Santarossa, Claudius Zelenka, Reinhard Koch
High-quality data is crucial for the success of machine learning, but labeling large datasets is often a time-consuming and costly process.
1 code implementation • 21 Jun 2023 • Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Reinhard Koch
While numerous methods exist to solve classification problems within curated datasets, these solutions often fall short in biomedical applications due to the biased or ambiguous nature of the data.
2 code implementations • 20 Feb 2024 • Tim Michels, Daniel Mäckelmann, Reinhard Koch
Our work addresses the often-overlooked role of the main lens exit pupil in these models and specifically in the decoding process of standard plenoptic camera (SPC) images.