姓名：庄黎
职称：讲师
电话：
办公室：
个人主页：
邮箱：lzhuang at seu dot edu dot cn
教育背景
博士（数据科学），香港城市大学，2020
学士（测控技术与仪器），华中科技大学，2016
学术兼职
研究领域
数据挖掘、机器学习和计算机视觉及其在智能交通、新能源领域的应用
研究概况
最近动态
研究课题
奖励与荣誉
课程信息
学术成果
L. Zhuang, H. Qi, T. Wang, and Z. Zhang, A deep learning powered near real-time detection of railway track major components: A two-stage computer vision based method, IEEE Internet of Things Journal, 2022.
R. Li, L. Zhuang*, Y. Li*, and C. Shen, Intelligent bearing fault diagnosis based on scaled ramanujan filter banks in noisy environments, IEEE Transactions on Instrumentation and Measurement, 2021.
L. Zhuang, H. Qi, Z. Zhang, The automatic rail surface multi-flaw identification based on a deep learning powered framework, IEEE Transactions on Intelligent Transportation Systems, 2021
Z. Zheng, H. Qi, L. Zhuang*, Z. Zhang*, Automated rail surface crack analytics using deep data-driven models and transfer learning, Sustainable Cities and Society, vol. 70, 2021.
L. Zhuang, L. Cao, Y. Wu, et al., Parameter estimation of lorenz chaotic system based on a hybrid jaya-powell algorithm, IEEE Access, vol. 8, pp. 20514–20522, 2020.
L. Zhuang, Z. Zhang, L. Wang, The automatic segmentation of residential solar panel s based on satellite images: A cross learning driven U-Net method, Applied Soft Computing, 92, 2020.
L. Wang, L. Zhuang, Z. Zhang, Automatic detection of rail surface cracks with a superpixel-based data-driven framework, Journal of Computing in Civil Engineering, vol. 33, 2018.
L. Zhuang, L. Wang, Z. Zhang, Automated vision inspection of rail surface cracks: A double-layer data-driven framework, Transportation Research Part C, vol. 92, pp. 258-277, 2018.
