Multi-mode Study of Deep Learning Applications in Acoustic Signal Processing. - Sheng Guan; Weicheng He; Wenjin Gu; Yuanzhao Hou; Yun Chen 001; Xiaoyang Zeng (SiPS, 2018)

Towards a Digital Twin Architecture with Formal Analysis Capabilities for Learning-Enabled Autonomous Systems. - Anastasios Temperekidis; Nikolaos Kekatos; Panagiotis Katsaros; Weicheng He; Saddek Bensalem; Hisham AbdElSabour; Mohamed Abdelsalam; Ashraf Salem (MESAS, 2022)

A digital twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle. - Mohamed Abdelsalam; Loai Ali; Saddek Bensalem; Weicheng He; Panagiotis Katsaros; Nikolaos Kekatos; Doron Peled; Anastasios Temperekidis; Changshun Wu (PoEM Companion, 2023)

Continuous Engineering for Trustworthy Learning-Enabled Autonomous Systems. - Saddek Bensalem; Panagiotis Katsaros; Dejan Nickovic; Brian Hsuan-Cheng Liao; Ricardo Ruiz Nolasco; Mohamed Abd El Salam Ahmed; Tewodros A. Beyene; Filip Cano 001; Antoine Delacourt; Hasan Esen; Alexandru Forrai; Weicheng He; et al. (AISoLA, 2023)

BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection. - Changshun Wu; Weicheng He; Chih-Hong Cheng; Xiaowei Huang 001; Saddek Bensalem (IROS, 2024)

Box-Based Monitor Approach for Out-of-Distribution Detection in YOLO: An Exploratory Study. - Weicheng He; Changshun Wu; Saddek Bensalem (RV, 2024)

Digital twin for the formal analysis of a depth of anesthesia controller. - Mohamed Abdelsalam; Saddek Bensalem; Antoine Delacourt; Weicheng He; Panagiotis Katsaros; Nikolaos Kekatos; Ricardo Ruiz Nolasco; Doron Peled; Matthieu Ponchant; Ismail Ryad; Anastasios Temperekidis; Changshun Wu (Simul., 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 001; Saddek Bensalem (CoRR, 2025)