一、个人简介:
刘业朋,男,博士,计算机科学与技术学院计算机科学与技术专业-专业负责人,硕士生导师。2010-2014,在山东大学计算机科学与技术学院,获工学学士学位;2014-2020,在山东大学计算机科学与技术学院,获工学博士学位,导师为张彩明教授;2021-至今,就职于山东工商学院计算机科学与技术学院。
联系方式:lyp@sdtbu.edu.cn。
二、研究方向:
[1].计算机图形学:主要涉及几何造型、几何建模与优化等方面的研究
[2].智能图形图像处理:主要涉及图像超分辨率、图像去噪、图像平滑和图像修复等方面的研究
[3].智能计算与金融大数据:主要涉及金融大数据智能分析与可视化、智能计算与风险控制等方面的研究
三、主讲课程:
[1].面向对象程序设计(本科生)
[2].移动软件开发(本科生)
[3].机器学习(本科生)
[4].高级计算机图形学(研究生)
四、科研项目:
[1].主持山东省自然科学基金青年项目:基于低秩拟合多尺度特征融合建模的图像修复关键技术研究,2022.1-2024.12,在研。
五、代表性论文:
[1].LiuYepeng,Li Xuemei, Zhang Xin, Zhang Caiming. Image enlargement method based on cubicsurfaces with local features as constraints - ScienceDirect[J]. SignalProcessing, 166:107266-107266. SCI 2 区, 影响因子4.662.
[2].LiuYepeng,Ma Xiang, Li Xuemei, Zhang Caiming. Two-stage image smoothing based onedge-patch histogram equalization and patch decomposition[J]. IET ImageProcessing,2020, 14(6): 1132-1140. SCI 4区,影响因子2.373.
[3].LiuYepeng, Li Xuemei, Guo Qiang, Zhang Caiming. AdaptiveIterative Global Image Denoising Method Based on SVD[J]. IET ImageProcessing,2020, 14(13): 3028-3038. SCI 4区,影响因子2.373.
[4].LiuYepeng, Zhang Fan, Zhang Yongxia, Li Xuemei Zhang Caiming.Image Smoothing Based on Histogram Equalized Content-aware Patches andDirection-constrained Sparse Gradients[J]. Signal Processing, 2021,183(4):108037. SCI 2 区, 影响因子4.662.
[5].WuLiqiong, Liu Yepeng, Brekhna, Liu Ning, Zhang Caiming.High-resolution images based on directional fusion of gradient[J].Computational Visual Media, 2016(1):13. EI
[6]. DingNa, Liu Yepeng, Fan Linwei, Zhang Caiming. Single ImageSuper-Resolution via Dynamic Lightweight Database with Local-Feature BasedInterpolation[J]. Journal of Computer Science and Technology, 2019,34(3):537-549. SCI 2 区, 影响因子1.571
[7].ZhouDanya, Liu Yepeng, Li Xuemei, Zhang Caiming. Single-imagesuper-resolution based on local biquadratic spline with edge constraints andadaptive optimization in transform domain[J]. The Visual Computer,2020(5):1-16. SCI 4区,影响因子2.601
[8].LiuJinlong, Liu Yepeng, Wu Heling, Wang Jiaye, Li Xuemei, ZhangCaiming. Single Image Super-Resolution Using Feature Adaptive Learning andGlobal Structure Sparsity[J]. Signal Processing, 2021(8):108184. SCI 2 区, 影响因子4.662.