简介


杨晶华,2020级人工智能博士生, 资讯科技学院,澳门科技大学,导师为戴宏宁教授陈川副教授。 硕士就读于电子科技大学数学科学学院。目前研究方向包括数据挖掘,图像处理、张量分析,深度学习。

邮箱: yangjinghua110@126.com
链接: Google Scholar

消息


学术论文

期刊 (发表)

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Meng Ding, Ting-Zhu Huang, “Tensor train rank minimization with hybrid smoothness regularization for visual data recovery”, Applied Mathematical Modelling, vol. 81, pp. 711-726, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Teng-Yu Ji, Tian-Hui Ma, Ting-Zhu Huang, “Low-rank tensor train for tensor robust principal component analysis”, Journal of Applied Mathematics and Computation, vol. 367, pp. 124783, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Yong Chen, Ting-Zhu Huang, Meng Ding, “Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization”, Journal of Computational and Applied Mathematics, vol. 363, pp. 124-144, 2020. [全文]

  • Jing-Hua Yang, Xi-Le Zhao, Tian-Hui Ma, Yong Chen, Ting-Zhu Huang, Meng Ding, “Total variation and high-order total variation adaptive model for restoring blurred images with Cauchy noise”, Journal of Computers and Mathematics with Applications, vol. 77, pp. 1255-1272, 2019. [全文]

  • Meng Ding, Ting-Zhu Huang, Tian-Hui Ma, Xi-Le Zhao, Jing-Hua Yang, “Cauchy noise removal using group-based low-rank prior”, Applied Mathematics and Computation, vol. 372, pp. 124971, 2020. [[全文] (https://MengDing56.gitHub.io/papers/20AMC_Nonlocal_Cauchy.pdf) [代码]

  • Meng Ding, Ting-Zhu Huang, Teng-Yu Ji, Xi-Le Zhao, Jing-Hua Yang, “Low-Rank Tensor Completion Using Matrix Factorization Based on Tensor Train Rank and Total Variation”, Journal of Scientific Computing, vol. 81, pp. 941–964, 2020. [全文] [代码]


教育背景

  • 09/2020-至今: 博士, 澳门科技大学 人工智能专业 (导师: 戴宏宁教授)

  • 09/2019-06/2020: 助教, 电子科技大学成都学院

  • 09/2016-06/2019: 硕士, 电子科技大学 数学专业 (导师: 赵熙乐教授)

  • 09/2012-06/2016: 本科, 太原师范学院 数学与应用数学专业


获奖情况

  • 一等学业奖学金 电子科技大学 2018

  • 一等学业奖学金 电子科技大学 2017