»姓名:齐玉娟 | »系属:自动化 | |
»学位:博士 | »职称:讲师 | |
»专业:控制理论与控制工程 | »导师类别:专硕 | |
»电子邮箱:qiyj@www.efhstore.com | ||
»联系电话:13687619557 | ||
»通讯地址:山东青岛市黄岛区长江西路66号 | ||
»概况 | ||
◎研究方向 模式识别、计算机视觉等。 ◎教育经历 2008.09~2012.12,爱游戏app官方入口 (华东),控制理论与控制工程,博士,导师:王延江 2000.09~2002.12,山东大学,控制理论与控制工程,硕士,导师:刘常春 1996.09~2000.07,山东工业大学,电气技术(师范),学士 ◎工作经历 2003.04~今,爱游戏app官方入口 (华东),控制科学与工程学院 ◎学术兼职 无 ◎主讲课程 《信号与系统》 ◎指导研究生及博士后 牛潇然,2012级,2015年6月毕业,论文题目:基于人类记忆机制的运动目标检测与跟踪方法研究 (注:协助王延江教授指导)。 刘昱池,2017级,(注:协助王延江教授指导) 刘梦雪,2019级 ◎承担项目 [1] 基于深度学习和人类记忆机制的运动目标提取和跟踪方法研究(No.ZR2017MF069),山东省自然科学基金面上项目,2017.08-2020.06,12万,主持,在研。 [2] 基于深度学习和人类记忆机制的运动目标跟踪方法研究(No.17CX02027A), 自主创新科研计划项目(理工科), 2017.01-2019.12,10 ,主持,在研。 [3] 基于人类记忆机制的多智能体协同进化鲁棒运动目标跟踪方法研究(No. ZR2013FQ015 ),山东省自然科学基金,2013.10-2016.10,5万, 主持,已结题。 [4] 核空间基于词典学习的多类分类方法研究(No.2016010033),自主创新科研计划项目(理工科),2016.1.1-2018.12.31,主要参与者,已结题。 [5] 再生核希尔伯特空间图像稀疏表达算法研究(No. 61402535),国家自然科学基金,2015.1-2017.12,主要参与者,已结题。 [6] 视觉注意与人脑记忆机制启发下的感兴趣目标提取与跟踪(No. 61271407),国家自然科学基金,2013.01-2016.12,主要参与者,已结题。 [7] 基于多视角学习的情感分析理论与方法研究(No.61301242), 国家自然科学基金,2014.1-2017.12,主要参与者,已结题 [8] 基于人类记忆机制的运动目标检测与跟踪方法研究( No.YCX2014056),爱游戏app官方入口 (华东)研究生创新工程,2014.6-2015.6. 主要参与者,已结题 [9] 基于人工生命和多智能体协同进化的多目标跟踪方法研究(No. 60873163),国家自然科学基金, 2009.01-2011.12, 主要参与者,已结题。 [10] 生物视觉机制启发下的人脸表情分析研究(ZR2011FQ016),2012.01-2015.12,4万元,山东省自然科学基金, 主要参与者,已结题。 [11] 基于人类记忆机制的运动目标鲁棒提取和跟踪方法研究(11CX06074A),中央高校基本科研业务费专项资金资助项目,2011.03-2013.04,主持,已结题。 [12] 人脑记忆机制启发下的视觉信息表达、存储与提取方法研究(14CX06067A),中央高校基本科研业务费专项资金资助项目,2013.06-2015.06 ,主要参与者,已结题 [13] 深度偏移中地震波粘滞效应的补偿研究,胜利油田物探院,2009-2010,骨干,已结题。 [14] 基于多源信息融合的钻井地质特征参数估计与预测方法研究(No.ZR2009FL029),山东省自然科学基金,2009-2012,骨干,已结题。 ◎获奖情况 2019 “新工科背景下《信号与系统》课程创新教学模式的探索与实践” 校级教学成果二等奖 2017 校优秀本科毕业设计 2020 校优秀本科毕业设计 ◎荣誉称号 ◎著作 视觉注意和人脑记忆机制启发下的感兴趣目标提取与跟踪(学术专著),科学出版社,2016.12(2/2) 信号与线性系统分析学习指导(校级十二五规划教材),爱游戏app官方入口 出版社,2017.11.(2/3) ◎论文 [1] Yanjiang Wang, Yujuan Qi. Memory-based Cognitive Modeling for Robust Object Extraction and Tracking. Applied Intelligence, 2013,39(13):614-629. [ EI:20133916770673, UT WOS: 000324107400011](通讯作者) [2] Yanjiang Wang,Yujuan Qi. Memory-based Multi-Agent Modeling for Robust Moving Object Tracking. The Scientific World Journal, Volume 2013, Article ID 793013, 13 pages,http://dx.doi.org/10.1155/2013/793013 [ UT WOS:000321360100001] (通讯作者) [3] 齐玉娟,王延江,李永平.基于记忆的混合高斯背景建模[J].自动化学报, 2010, 36(11):1520-1526. [EI :20105013489733] [4] 王延江,李蕙,齐玉娟. 一种受人脑三阶段记忆机制启发的鲁棒运动目标跟踪方法.电子学报,OCT. 2017,45(9):2065-2070 [EI:20174404325845](通讯作者) [5] 齐玉娟,牛潇然,王延江. 基于人类记忆机制的码本建模方法研究[J].爱游戏app官方入口 学报(自然科学版),2015,39(4):178-184。[EI:20153401187923] [6] 齐玉娟,王延江.基于人类记忆模型的粒子滤波鲁棒目标跟踪算法[J].模式识别与人工智能, 2012, 25(5):810-816.[EI: 20125115818466] [7] Yujuan Qi, Yanjiang Wang. Memory-based Template Updating for Robust Object Tracking by Mean-shift[J].International Journal of Advancements in Computing Technology, 2012,4(13):378-389.[EI :20123515378579] [8] 齐玉娟,王延江. 一种基于混合高斯的双空间自适应背景建模方法[J].爱游戏app官方入口 学报(自然科学版),2012, 36(5):175-178.[ EI:20124815732337] [9] 齐玉娟,王延江. 基于记忆的多智能体鲁棒运动目标跟踪建模.山东科技大学学报(自然科学版),2013,32(3):22-27 [10] 王延江,齐玉娟. .基于人类记忆机制的视觉信息处理认知建模[J]. 模式识别与人工智能, 2013,26(2): 144-150. [11] Yujuan Qi, Yanjiang Wang. Human Memory Inspired Gaussian Mixture Background Modeling for Dynamic Scenes with Sudden Partial Changes[J]. International Journal of Digital Content Technology and its Applications, 2013,7(1):74-84. [12] Yanjiang Wang, Yujuan Qi. Psychologically Inspired Information Storage and Retrieval Modeling based on the Three-Stage Memory Mechanism of Human Brian[J]. Journal of Computational Information Systems, 2013,9(4):1473-1481.[EI: 20131516191876] [13] 李永平,王延江,齐玉娟. 基于多智能体协同进化的粒子滤波目标跟踪算法[J]. 模式识别与人工智能,2011,24(1):57-63. [EI: 20111713935681] [14] Yujuan Qi, Yanjiang Wang, Tingting Xue. Brain Memory Inspired Template Updating Modeling for Robust Moving Object Tracking Using Particle Filter[A].Proceedings of BICS[C], 2012, Lecture Notes in Artificial Intelligence (LNAI :7366), Shenyang, China, 2012.07.11-14. [EI:20123515371761] [15] Yujuan Qi,Yanjiang Wang, Xiaoran Niu, Spinning Tri-Layer-Circle Memory Modeling for Template Updating During Moving Object Tracking[A], Proc. Of 2014 IEEE International Conference on Systems, Man, and Cybernetics[C], October 5-8, 2014, San Diego, CA, USA:2877-2882[EI:20153101092892] [16] Yujuan Qi, Li Hui, Yanjiang Wang, Baodi Liu. Spinning Tri-Layer-Circle Memory-based Gaussian Mixture Model for Background Modeling. Proc. Of 2016 13th International Conference on Signal Processing (ICSP2016), Nov. 6-10, 2016, Chengdu, Sichuan, China, pp. 943-948[EI: 20171403516704] [17] Yujuan Qi,Yanjiang Wang, Yuchi Liu. Object Tracking Based on Deep CNN Feature and Color Feature. Proc. Of 2018 14th International Conference on Signal Processing (ICSP2018), Aug. 12-16, 2018, Beijing, China, pp. 469-473. [18] Shuangkang Fang,Yujuan Qi.A Target Tracking Method based on Particle Filter and Multi-feature Fusion. Proc. Of 2018 14th International Conference on Signal Processing (ICSP2018), Aug. 12-16, 2018, Beijing, China, pp. 464-468. [19] Xiaoran Niu, Yanjiang Wang, Yujuan Qi. Memory-based particle filter for real time object tracking[A],proceedings of 2014 IEEE Conference on Signal Processing[C], 2014,vol.1, October 19-23, 2014 ,Hangzhou, China,pp909-912. [EI:20153101078010] [20] Xiaoran Niu, Yanjiang Wang, Yujuan Qi. Memory-based codebook model for real-time object detection[A],proceedings of 2014 IEEE Conference on Signal and Processing[C],2014,vol.1, October 19-23, 2014, Hangzhou, China, pp.913-917. [EI:20153101078449] [21] Yujuan Qi, Yanjiang Wang. Visual Tracking with Double-layer Particle Filter[A]. Proceedings of 11th IEEE International Conference on Signal Processing[C], Beijing, China, October 21, 2012 - October 25, 2012, 2:1127-1130.[EI: 20131716243026] [22] Yujuan Qi, Yanjiang Wang. Memory-based state estimation for handling occlusion during object tracking by particle filter[A]. Proceedings of 1st International Conference on Information Science and Technology[C],March26-28, Nanjing, Jiangsu, China, 2011,4: 953-957. [EI:20112314027394] [23] Yujuan Qi, Yanjiang Wang. Memory-based Gaussian Mixture Modeling for Moving Object Detection in Indoor Scene with Sudden Partial Changes[A]. Proceedings of 10th IEEE International Conference on Signal Processing[C], October 25-27, Beijing, China, 2010,2:752-755 [EI:20110213573671] [24] Chuan Gu, Yanjiang Wang, Yujuan Qi. Ghosts and Stationary Foreground Detection by Dual-Direction Background Modeling[A]. Proceedings of 11th IEEE International Conference on Signal Processing [C], Beijing, China, Oct. 2012,2:1115-1118.[EI: 20131716243023] [25] Tingting Xue, Yanjiang Wang, Yujuan Qi. Multi-Feature Fusion Based GMM for Moving Object and Shadow Detection[A].Proceedings of 11th IEEE International Conference on Signal Processing [C], Beijing,China, Oct. 2012 2:1119-1122.[EI: 20131716243024] [26] Tingting Xue, Yanjiang Wang, Yujuan Qi. Tracking Multi Objects With Different Size Based on Data Association[A]. Proceedings of 11th IEEE International Conference on Signal Processing [C], Beijing, China, Oct. 20122:1123-1126.[EI: 20131716243025] [27] Yanjiang Wang, Wenjuan Wang, Yujuan Qi, Hui Li. A novel fast human face searching algorithm based on evolutionary agent[A]. Proceedings of 10th IEEE International Conference on Signal Processing,Beijing[C], China,October 25-27,2010, 2:653-656. [EI: 20110213573943] [28] Yujian Qi,Yanjiang Wang, Peng Suo. An Improved Background Mixture Model for Robust Moving Object Segmentation[A].Proceedings of 1th International Conference on Information Science and Engineering Proceedings[C], Dec. 18-19,2009, LNCS: E3887, 4: 115-118.[EI:20102212964321] [29] Yanjiang Wang, Peng Suo, Yujuan Qi. Memorizing GMM to handle sharp changes in moving object segmentation[A].Proceedings of the 2009 2nd International Congress on Image and Signal Processing[C], October 17-19,2009 [EI: 20100212631285] [30] Yongping Li, Yanjiang Wang, Yujuan Qi, Hui Li. Multi-agent based particle filter for moving object tracking[A].Proceedings of IEEE International Conference on Computer Application and System Modeling(ICCASM 2010),Taiyuan,Shanxi, China, Oct.2010, 4 :124-127.[EI: 20104913452218] [31] 王延江,齐玉娟. 基于记忆机制的视觉信息处理建模[A]. 2011中国自动化大会, 2011.11.26-29,北京. ◎专利 无 |