7 papers
Autonomous Unmanned Aircraft Systems for Enhanced Search and Rescue of Drowning Swimmers: Image-Based Localization and Mission Simulation
Sascha Emanuel Zell, Toni Schneidereit, Armin Fügenschuh +1
Drowning is an omnipresent risk associated with any activity on or in the water, and rescuing a drowning person is particularly challenging because of the time pressure, making a s…
Strategies for training point distributions in physics-informed neural networks
Santosh Humagain, Toni Schneidereit
Physics-informed neural networks approach the approximation of differential equations by directly incorporating their structure and given conditions in a loss function. This enable…
Object detection characteristics in a learning factory environment using YOLOv8
Toni Schneidereit, Stefan Gohrenz, Michael Breuß
AI-based object detection, and efforts to explain and investigate their characteristics, is a topic of high interest. The impact of, e.g., complex background structures with simila…
YOLO-based Object Detection in Industry 4.0 Fischertechnik Model Environment
Slavomira Schneidereit, Ashkan Mansouri Yarahmadi, Toni Schneidereit +2
In this paper we extensively explore the suitability of YOLO architectures to monitor the process flow across a Fischertechnik industry 4.0 application. Specifically, different YOL…
Adaptive neural domain refinement for solving time-dependent differential equations
Toni Schneidereit, Michael Breuß
A classic approach for solving differential equations with neural networks builds upon neural forms, which employ the differential equation with a discretisation of the solution do…
Collocation Polynomial Neural Forms and Domain Fragmentation for solving Initial Value Problems
Toni Schneidereit, Michael Breuß
Several neural network approaches for solving differential equations employ trial solutions with a feedforward neural network. There are different means to incorporate the trial so…
Computational characteristics of feedforward neural networks for solving a stiff differential equation
Toni Schneidereit, Michael Breuß
Feedforward neural networks offer a promising approach for solving differential equations. However, the reliability and accuracy of the approximation still represent delicate issue…