Florian Liebgott's research while affiliated with Universität Stuttgart and other places
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publications (10)
To achieve a high overall equipment effectiveness in a manufacturing process, reducing the number of defective units is crucial. It is therefore vital to identify the root causes of defects to be able to rectify them. However, the analysis of defective units can be a time-consuming and costly task.
By using machine learning, we can leverage data of...
Modern production of fiber reinforced composites via the preforming process is widely used in the industry. A common way to create dry, semi-finished fiber products is forming or draping a textile into a three-dimensional component geometry. The punch and die process is often used for resin transfer molding (RTM) composite manufacturing. Due to the...
In production environments, monitoring the vibration of a machine or parts thereof can yield important information about the condition of the machine. The most common recommendation for vibration-based condition monitoring is to place a vibration sensor on each part of interest. These vibration sensors usually output preprocessed data, for example...
In high-field whole body magnetic resonance imaging (MRI), images usually suffer from intensity inhomogeneities. The BC-FAT (bias correction by fitting of adipose tissue intensity) algorithm can compensate for this; however, it is limited to images containing only one object, e.g. the torso. In this paper, we present a method, which extends the BC-...
Citations
... In a previous study we proposed a feature-based machine learning approach to locate regions of especially high SUVs within CT images of lung tumors [5], which is described in section II of this paper. Since the ultimate goal of our work is to generate detailed PET-like images and our first approach was not suitable for this task, we decided to investigate the ability of generative adversarial networks (GANs) [6] to create a more realistic estimation of variations in FDG uptake within a tumor from CT input data. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/785325936873472-1564247702137_Q64/Annika-Liebgott.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272324716920882-1441938680934_Q64/Yang-Bin-11.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/703827359567878-1544816927532_Q64/Sergios-Gatidis.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/323259164233729-1454082398498_Q64/Konstantin-Nikolaou.jpg)
... AL for NILM has not been extensively investigated yet -there have only been a few attempts for event-based methods using high-frequency load measurements, based on: k-Nearest Neighbours (k-NN) in [54], Support Vector Machines (SVM) in [55], Random Forest with semi-supervised and AL combined in [56], and a DNN, using high-frequency measurements and event detection in [57], and only one approach using low-frequency measurements and supervised model-based NILM in [46]. However, in [46], only strong labels are used, which can be hard to obtain from end users in a real-world scenario. ...
