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刘业朋
2024-11-05 17:05     (阅读)

个人简介:

 刘业朋,计算机科学与技术专业专业负责人,硕士生导师。担任IEEE Transactionson Image Processing (TIP), IEEE Transactions on Circuits and Systems for Video Technology(TCSVT),  Pattern Recognition(PR)Information Science 

等期刊的审稿人,博士生导师张彩明教授。

联系方式:lyp@sdtbu.edu.cn

2010.09-2014.06,山东大学计算机科学与技术学院,获工学学士学位; 

2014.09-2020.12,山东大学计算机科学与技术学院,获工学博士学位; 

2021.01-2023.12,山东工商学院计算机科学与技术学院,讲师; 

2023.09-2024.08,中国科学院烟台海岸带研究所,访学;

2024.01-至今,山东工商学院计算机科学与技术学院,副教授。 

 

研究方向:

[1].计算机图形学

涉及几何造型、几何建模与优化等方面 

[2].图像处理

自然图像处理:涉及图像超分辨率、去噪、平滑和修复等

医学图像处理:涉及单目标、多目标医学图像分割

遥感图像处理:涉及遥感图像变化检测

[3].时间序列预测

时序短期预测:涉及金融大数据预测、智能分析与可视化等

时序长期预测:涉及电力、天气、汇率、交通流量等的预测

 

主要讲授课程:

[1] 深度学习(研究生)

[2] 高级计算机图形学(研究生)

[3] 学术规范与论文写作(研究生)

[4] 机器学习(本科生)

[5] 大数据导论(本科生)

[6] 面向对象程序设计(本科生)

[7] 操作系统、操作系统课程设计(本科生)

[8] 移动软件开发、企业项目综合实训II(本科生)

 

科研项目:

[1].国家自然科学基金浙江联合基金重点项目:智慧医疗中大数据分析的基础理论和语义融合技术,2017.1-2021.12,参与,已结题。

[2].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,主持,在研。

[3].山东捷瑞数字技术开发成果转化,2022.6-2022.9,主持,完结(横向)。

[4].山东工商学院财富管理跨学科交叉研究项目:“区块链+物联网供应链金融智能化研究,2023.1-2024.12,主持,在研。

 

代表性论文:

第一或通讯作者

[1].SiyuanHuang, Yepeng Liu∗, et al . MEAformer:An all-MLP Transformer with Temporal External Attention for Long-term TimeSeries Forecasting [J]. Information Sciences,2024, 669:120605. SCI 1.

[2]. SiyuanHuang, Yepeng Liu. FL-Net: Amulti-scale cross-decomposition network with frequency external attention forlong-term time series forecasting[J]. Knowledge-Based Systems, 2024: 111473. SCI1.

[3]. ZhenyangHuang, Yixing Zhao, Jinjiang Li, Yepeng Liu*. Bgman:Boundary-Prior-Guided Multi-scale Aggregation Network for skin lesion segmentation[J].International Journal of Machine Learning and Cybernetics, 2024: 1-20. SCI 3.

[4]. Yu Shangguan,Jinjiang Li, Yepeng Liu*, Fan Zhang, Caiming Zhang. Attentionfiltering network based on branch transformer for Change Detection in Remote SensingImages[J]. IEEE Transactions on Geoscience and Remote Sensing.vol.62, pp. 1-19, 2024, doi: 10.1109/TGRS.2023.3345645. SCI 1. 

[5]. YepengLiu, Siyuan Huang, Xiaoyi Tian, Fan Zhang,Feng Zhao, Caiming Zhang, A stock series prediction model based on variationalmode decomposition and dual-channel attention network[J].ExpertSystems With Applications, 2024, 238:121708,SCI 1. 

[6]. SiyuanHuang, Yepeng Liu, Fan Zhang, YueLi, Jinjiang Li, Caiming Zhang. CrossWaveNet: A Dual-Channel Network with DeepCross-Decomposition for Longterm Time Series Forecasting[J].ExpertSystems With Applications, 2024, 238:121642,SCI 1. 

[7]. JunyuFan, Jinjiang Li, Yepeng Liu*, Fan Zhang. Frequency-aware robustmultidimensional information fusion framework for remote sensing imagesegmentation[J]. Engineering Applications of Artificial Intelligence, 2024,129: 107638, SCI 2.

[8]. YiyangZhao, Xinyang Song, Jinjiang Li, Yepeng Liu*. CSCNet: ACross-Scale Coordination Siamese Network for Building Change Detection[J]. IEEEJournal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.17, pp. 1377-1389, 2024, doi: 10.1109/JSTARS.2023.3337999. SCI 2.

[9]. YepengLiu*,Dezhi Yang, Fan Zhang, Qingsong Xie, Caiming Zhang. Deep Recurrent ResidualChannel Attention Network for Single Image Super-resolution[J]. The VisualComputer, 2023,DOI:10.1007/s00371-023-03044-0. SCI 3.

[10]. YiyangZhao, Jinjiang Li, Yepeng Liu*. Dynamic Weight HiLo AttentionNetwork for Medical Image Multiple Organ Segmentation[J]. International Journalof Imaging Systems and Technology, 2023, DOI:10.1002/ima.22966.SCI 4. 

[11]. 刘业朋*,杨得志, 李思远, 张帆, 张彩明. 基于图像分解和相对全变分的图像平滑[J]. 图学学报, 2022, 43(6):7, CSCD. 

[12]. YepengLiu, FanZhang, Yongxia Zhang, Xuemei Li, Caiming Zhang*. Image Smoothing Based onHistogram Equalized Content-aware Patches and Direction-constrained SparseGradients[J]. Signal Processing, 2021, 183(4):108037. SCI 2 .

[13]. YepengLiu,Xuemei Li, Xin Zhang, Caiming Zhang *. Image enlargement method based on cubicsurfaces with local features as constraints[J]. Signal Processing, 2020,166:107266-107266. SCI 2 .

[14]. YepengLiu, XuemeiLi*, Qiang Guo, Caiming Zhang. Adaptive Iterative Global Image Denoising MethodBased on SVD[J]. IET Image Processing,2020, 14(13): 3028-3038. SCI 4.

[15]. YepengLiu,Xiang Ma, Xuemei Li *, Caiming Zhang. Two-stage image smoothing based onedge-patch histogram equalization and patch decomposition[J]. IET ImageProcessing,2020, 14(6): 1132-1140. SCI 4.

 

其他论文

[16]. Lin Li,Hua Wang, Yepeng Liu, Fan Zhang*. Probabilistic interval predictionmethod based on shape-adaptive quantile regression[J]. Expert Systems, doi:10.1111/exsy.13585.2024, SCI 4.

[17]. MingyanZhang, Mingli Zhang, Feng Zhao, Fan Zhang, Yepeng Liu, AlanEvans. Truncated Weighted Nuclear Norm Regularization and Sparsity for ImageDenoising[C]//2023 IEEE International Conference on Image Processing (ICIP).IEEE, 2023: 1825-1829.

[18]. TiantianGuo, Hua Wang, Mingli Zhang, Yepeng Liu, Fan Zhang*. Fast andhighly coupled model for time series forecasting. Multimedia Tools andApplications, 2023, DOI:10.1007/s11042-023-15787-y, SCI 4 . 

[19]. GongguanChen, Hua Wang, Yepeng Liu, Mingli Zhang, Fan Zhang*. Resformer:Combine quadratic linear transformation with efficient sparse Transformer forlong-term series forecasting. 2023, SCI 4 .

[20]. JinlongLiu, Yepeng Liu, Heling Wu, Jiaye Wang, Xuemei Li, Caiming Zhang*.Single Image Super-Resolution Using Feature Adaptive Learning and GlobalStructure Sparsity[J]. Signal Processing, 2021(8):108184. SCI 2 .

[21]. DanyaZhou, Yepeng Liu, Xuemei Li*, Caiming Zhang. 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 3.

[22]. Na Ding,Yepeng Liu, Linwei Fan, Caiming Zhang*. 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 .

[23]. LiqiongWu, Yepeng Liu, Brekhna, Ning Liu, Caiming Zhang*.High-resolution images based on directional fusion of gradient[J].Computational Visual Media, 2016(1):13. EI

 

专利:

[1].基于九曲面片双四次拟合的图像放大方法和装置,ZL202210683222.22023(第一发明人)。

[2].火焰切割装置的切割控制方法,ZL202111281385.X2022(第三发明人)。

[3].基于深度递归残差通道注意力的图像放大方法,2023(第一发明人,实质审查)。

[4].基于变分模态分解和双通道自注意力的电力负荷预测方法,2023(第一发明人,实质审查)。

[5].基于深度交叉分解的双通道电力负荷预测方法, 2024(第二发明人,实质审查)。

[6].基于分片分解和直方图均衡化的两阶段图像平滑方法,2024(第一发明人,实质审查)。 

指导研究生:

2021级:李思远、杨得志(协助指导)

2022级:黄思远、田晓艺

2023级:黄志根、曾家福、刘飞宇

2024级:徐润萱、孟宪鹏、王舒洁、王唯一、赵彤彤

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