7 citations · 11 across the 4 of their papers we have counts for
6 papers
Deep Domain Adaptation for Detecting Bomb Craters in Aerial Images
Marco Geiger, Dominik Martin, Niklas Kühl
The aftermath of air raids can still be seen for decades after the devastating events. Unexploded ordnance (UXO) is an immense danger to human life and the environment. Through the…
Deep Learning Strategies for Industrial Surface Defect Detection Systems
Dominik Martin, Simon Heinzel, Johannes Kunze von Bischhoffshausen +1
Deep learning methods have proven to outperform traditional computer vision methods in various areas of image processing. However, the application of deep learning in industrial su…
Towards a Reference Architecture for Future Industrial Internet of Things Networks
Dominik Martin, Niklas Kühl, Marcel Schwenk
With the continuing decrease of sensor technology prices as well as the increase of communication and analytical capabilities of modern internet of things devices, the continuously…
Human vs. supervised machine learning: Who learns patterns faster?
Niklas Kühl, Marc Goutier, Lucas Baier +2
The capabilities of supervised machine learning (SML), especially compared to human abilities, are being discussed in scientific research and in the usage of SML. This study provid…
"Healthy surveillance": Designing a concept for privacy-preserving mask recognition AI in the age of pandemics
Niklas Kühl, Dominik Martin, Clemens Wolff +1
The obligation to wear masks in times of pandemics reduces the risk of spreading viruses. In case of the COVID-19 pandemic in 2020, many governments recommended or even obligated t…
A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs
Dominik Martin, Philipp Spitzer, Niklas Kühl
Forecasts of product demand are essential for short- and long-term optimization of logistics and production. Thus, the most accurate prediction possible is desirable. In order to o…