no code implementations • 31 Aug 2023 • Johannes Künzel, Anna Hilsmann, Peter Eisert
We introduce BTSeg, an innovative, semi-supervised training approach enhancing semantic segmentation models in order to effectively handle a range of adverse conditions without requiring the creation of extensive new datasets.
no code implementations • 6 Mar 2023 • Johannes Künzel, Darko Vehar, Rico Nestler, Karl-Heinz Franke, Anna Hilsmann, Peter Eisert
The assessment of sewer pipe systems is a highly important, but at the same time cumbersome and error-prone task.
no code implementations • 1 Feb 2022 • Clemens Seibold, Johannes Künzel, Anna Hilsmann, Peter Eisert
The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision.
Explainable Artificial Intelligence (XAI) Image Segmentation +3
no code implementations • 11 Dec 2019 • Johannes Künzel, Thomas Werner, Ronja Möller, Peter Eisert, Jan Waschnewski, Ralf Hilpert
The task of detecting and classifying damages in sewer pipes offers an important application area for computer vision algorithms.