Weicheng He — accepted AI-conference papers

2025

Mitigating Hallucinations in YOLO-based Object Detection Models: A Revisit to Out-of-Distribution Detection

Weicheng He, Changshun Wu, Chih-Hong Cheng, Xiaowei Huang, Saddek Bensalem

IROS 2025

Object detection systems must reliably perceive objects of interest without being overly confident to ensure safe decision-making in dynamic environments. Filtering techniques based on out-of-distribution (OoD) detection are commonly added as an extra safeguard to filter hallucinations caused by ove

Cited by 3 Source ↗Scholar ↗

2024

BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection

Changshun Wu, Weicheng He, Chih-Hong Cheng, Xiaowei Huang, Saddek Bensalem

IROS 2024poster

Out-of-distribution (OoD) detection techniques for deep neural networks (DNNs) become crucial thanks to their filtering of abnormal inputs, especially when DNNs are used in safety-critical applications and interact with an open and dynamic environment. Nevertheless, integrating OoD detection into st…

Cited by 3 Source ↗Scholar ↗