Search Results for author: Raoul Schönhof

Found 3 papers, 1 papers with code

Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder

1 code implementation21 Feb 2022 Raoul Schönhof, Jannes Elstner, Radu Manea, Steffen Tauber, Ramez Awad, Marco F. Huber

In this work, we present a deep residual 3D autoencoder based on the EfficientNet architecture, intended for transfer learning tasks related to 3D CAD model assessment.

Transfer Learning

Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods

no code implementations28 Jan 2022 Raoul Schönhof, Artem Werner, Jannes Elstner, Boldizsar Zopcsak, Ramez Awad, Marco Huber

Explainable AI methods have been used in order to assess whether a neural network has successfully learned a given task or to analyze which features of an input might lead to an adversarial attack.

Adversarial Attack Explainable artificial intelligence +1

Towards automated Capability Assessment leveraging Deep Learning

no code implementations28 Jan 2022 Raoul Schönhof, Manuel Fechter

Aiming for a higher economic efficiency in manufacturing, an increased degree of automation is a key enabler.

Position

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