Dr. rer. nat.

Cheng, Chih-Hong

Filters

2
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Statistical Guarantees for Safe 2D Object Detection Post-processing
    ( 2023)
    Seferis, Emmanouil
    ;
    Burton, Simon
    ;
    Kollias, Stefanos
    ;
    Cheng, Chih-Hong
    Safe and reliable object detection is essential for safetycritical applications of machine learning, such as autonomous driving. However, standard object detection methods cannot guarantee their performance during operation. In this work, we leverage conformal prediction in order to provide statistical guarantees for back-box object detection models. Extending prior work, we present a postprocessing methodology that can cover the entire object detection problem (localization, classification, false negatives, detection in videos, etc.), while offering sound safety guarantees on its error rates. We apply our method on state-of-the-art 2D object detection models and measure its efficacy in practice. Moreover, we investigate what happens as the acceptable error rates are pushed towards high safety levels. Overall, the presented methodology offers a practical approach towards safety-aware object detection, and we hope it can pave the way for further research in this area.
  • Publication
    Intelligent Testing for Autonomous Vehicles - Methods and Tools
    ( 2022-09)
    Cheng, Chih-Hong
    In this talk, I first give a tutorial on some fundamental AI testing methods with their strengths and weaknesses. For testing complex autonomous driving systems, an intelligent combination of basic AI testing techniques makes it possible to generate highly diversified test cases while enabling efficient bug hunting.