+49 208 882 54 - 829 anselm.haselhoff@hs-ruhrwest.de

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anselm.haselhoff@hs-ruhrwest.de

Reliable and transparent artificial intelligence for automotive and industrial applications

  • Home
  • Publications
  • Courses
  • Team
  • Contact

Dependency Decomposition and a Reject Option for Explainable Models

Deploying machine learning models in safety-related domains (e.g. autonomous driving, medical diagnosis) demands for approaches that are explainable, robust against adversarial attacks and aware of the model uncertainty. Recent deep learning models perform extremely well…

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Markov random field for image synthesis with an application to traffic sign recognition

In current state-of-the-art systems for object detection and classification a huge amount of data is needed. Even if large databases are available, some classes are typically underrepresented and therefore the classifier is not able to…

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Computer Science Institute
Ruhr West University of Applied Sciences

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