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YOLO-based Object Detection in Industry 4.0 Fischertechnik Model Environment
In this paper we extensively explore the suitability of YOLO architectures to monitor the process flow across a Fischertechnik industry 4. 0 application.
Adaptive neural domain refinement for solving time-dependent differential equations
In the present work, we propose a novel adaptive neural approach to meet this aim for solving time-dependent problems.
Collocation Polynomial Neural Forms and Domain Fragmentation for solving Initial Value Problems
Several neural network approaches for solving differential equations employ trial solutions with a feedforward neural network.
Computational characteristics of feedforward neural networks for solving a stiff differential equation
Computational approaches are in general highly dependent on a variety of computational parameters as well as on the choice of optimisation methods, a point that has to be seen together with the structure of the cost function.
