Driving skill analysis using machine learning The full curve and curve segmented cases. - Naiwala P. Chandrasiri; Kazunari Nawa; Akira Ishii; Shuguang Li 004; Shigeyuki Yamabe; Takayuki Hirasawa; Yoichi Sato 001; Yoshihiro Suda; Takeshi Matsumura; Koji Taguchi (ITST, 2012)

Learning Characteristic Driving Operations in Curve Sections that Reflect Drivers' Skill Levels. - Shuguang Li 004; Shigeyuki Yamabe; Yoichi Sato 001; Yoshihiro Suda; Naiwala P. Chandrasiri; Kazunari Nawa (Int. J. Intell. Transp. Syst. Res., 2014)

Depth Estimation via Sparse Radar Prior and Driving Scene Semantics. - Ke Zheng; Shuguang Li 004; Kongjian Qin; Zhenxu Li; Yang Zhao 024; Zhinan Peng; Hong Cheng 002 (ACCV (2), 2022)

Vehicle-in-the-Loop Intelligent Connected Vehicle Simulation System Based on Vehicle-Road-Cloud Collaboration. - Shuguang Li 004; Zhonglin Luo; Wenbo Wei; Yang Zhao 024; Jierui Hu; Hong Cheng 002 (ITSC, 2022)

An Object Detection Method Enhanced by Sparse Point Cloud for Low Illumination in Autonomous Driving. - Shuguang Li 004; Bei Liu; Yang Zhao 024; Ke Zheng; Hong Cheng 002 (ITSC, 2022)

Radar-Camera Fusion Network for Depth Estimation in Structured Driving Scenes. - Shuguang Li 004; Jiafu Yan; Haoran Chen; Ke Zheng (Sensors, 2023)

A lightweight neural network search algorithm based on in-place distillation and performance prediction for hardware-aware optimization. - Siyuan Kang; Yinghao Sun; Shuguang Li 004; Yaozong Xu; Yuke Li; Guangjie Chen; Fei Xue (Eng. Appl. Artif. Intell., 2025)

A Bidirectional Iterative and Synergistic Supervision Approach for Infrared-Visible Image Registration. - Jiafu Yan; Changhua Zhang; Qingkun Li; Bin Liu 067; Shuguang Li 004 (IEEE Trans. Instrum. Meas., 2025)