• Explainable parts-based concept modeling and reasoning 

    Ruprecht, Blake (University of Missouri--Columbia, 2023)
    State-of-the-art artificial intelligence (AI) learning algorithms heavily rely on deep learning methods that exploit correlation between inputs and outputs. While effective, these methods typically provide little insight ...
  • Human-assisted self-supervised labeling of large data sets 

    Schulz, Jeffrey (University of Missouri--Columbia, 2022)
    There is a severe demand for, and shortage of, large accurately labeled datasets to train supervised computational intelligence (CI) algorithms in domains like unmanned aerial systems (UAS) and autonomous vehicles. This ...