UseML (IKT of the Future)

The overall goal of the project is to enable the end-user to adequately deal with the complexity of automatic inspection systems during the set-up phase and during maintenance.  The project aims at the following goals:

• Active learning and in-line training:
  • developing methodologies which reduce the requested number of class labels during off-line training and on-line adaptation of classifiers
  • synthesizing artificial defect images that can be presented to acquire input in areas, where no real samples could yet be obtained
  • detecting a systematic change in the decision making (concept drift) and to efficiently update or correct earlier decision without the need of re-labelling a large part of the previous samples.
     
• Adding new defect classes:
  • acquiring high-level information about the defect class from the end-user in the presence of very little concrete data
  • data base search for similar samples and refining decision boundaries
     
• Explaining and correcting false decisions:
  • making progress in interpretability and representation of classifiers
  • enabling the user to modify structural components and decision boundaries
  • addressing reliability concepts (interpretability of classifiers outputs, reason finding)