李 琦铭，副研究员/硕导，博士毕业于厦门大学计算机科学与技术专业，福建省高层次人才（B类），曾获澳门银银河“春苗”青年人才、“精英博士后”等荣誉称号。主要从事计算机视觉﹑目标检测与跟踪、人机交互及机器学习等方面的研究工作。主持过国家自然科学基金、中国博士后科学基金、福建省自然科学基金、泉州市科技计划及企业横向合作等多个项目，参与国家重点研发计划、福建省科技重大专项、中科院STS等多个重点项目。受邀担任IEEE TIE,IEEE ITSM,IEEE TITS等国际知名期刊审稿人，在国际和国内学术期刊和会议上发表论文30余篇，拥有专利10余项。

招生方向：计算机视觉、机器学习

联系方式：qimingli@fjirsm.ac.cn

近年代表作：

[1] Qiming Li,Yijing Su,Ying Gao,Feng Xie,and Jun Li^*. Learning geometric information via

Transformer network for key-points based motion segmentation,IEEE Transactions on Circuits and Systems for Video Technology,2024,DOI:10.1109/TCSVT.2024.3382363.

[2] Jun Li,Yuquan Bi,Sumei Wang,Qiming Li^*. CFRLA-Net: A context-aware feature representation learning anchor-free network for pedestrian detection. IEEE Transactions on Circuits and Systems for Video Technology,2023,33(9):4948-4961.

[3] Qiming Li,Yijing Su,Ying Gao,Feng Xie,and Jun Li^*. OAF-Net: An occlusion-aware anchor-free network for pedestrian detection in a crowd,IEEE Transactions on Intelligent Transportation Systems,2022,23(11):21291-21300.

[4] Qiming Li,Hua Qiang,and Jun Li^*. Conditional random fields as message passing mechanism in anchor-free network for multi-scale pedestrian detection,Information Sciences,2021:1-12.

[5] Qiming Li,Hanzi Wang^*,Yan Yan,Bo Li,and ChangWen Chen. Local co-occurrence selection via partial least squares for pedestrian detection. IEEE Transactions on Intelligent Transportation Systems,2017,18(6):1549-1588.