张娟

发布者:沈怡君发布时间:2017-08-08浏览次数:7174

导师简介

姓  名

张娟

性  别

职  称

副教授

研究方向

计算机视觉、人工智能

通讯地址

上海市松江区龙腾路333

邮政编码

201620

联系电话

15821712631

电子邮箱

zhang-j@foxmail.com

张娟,工学博士,副教授,硕士生导师。2012年毕业于上海大学,获工学博士学位,2014年上海大学信息与通信工程博士后流动站出站。曾参于国家高技术研究发展计划项目(863计划)《面向多行业IT资源库的建设及应用》、国家自然科学基金项目《面向物体级的视觉SLAM动态三维场景解析与重建》、《基于SXM模型的Web软件测试理论与方法》及2项省市级科研项目的研究工作。已公开发表学术论文近30余篇,其中SCI收录10余篇,为研究生和本科生开设了《机器学习》、《图像处理》、《计算机网络》、《计算机图形学》、《数据库原理》、《软件测试》等课程。

主要成果

【获奖情况】

  1. 跨相机智能视频处理与分析关键技术及其产业化,上海市科学技术奖,二等奖,上海市人民政府.


【专著】

  1. 《英汉云计算•物联网•大数据辞典》及简明词典,An English-Chinese Cloud Computing IOT Big Data Dictionary,副主编,上海交通大学出版社2018ISBN978-7-313-18433-7/G.

  2. 软件测试中测试用例复用的研究,独著,哈尔滨工业大学出版社,20228月第一版,ISBN978-7-5767-0481-1.


【标准】

  1. 国际标准《Guide for Scientific Knowledge Graph》,立项号:IEEE Standard  P2807.4 IEEE电气电子工程师学会。

  2. 国家标准《信息技术 人工智能 知识图谱技术框架》,GB/T 20192137-T-469,已实施。


【纵向项目】

  1.  多源特征融合的主动式行车安全分析与预警平台,上海市科委地方院校能力建设项目,项目编号:15590501300

  2. 面向物体级的视觉SLAM动态三维场景解析与重建,国家自然科学基金项目,项目编号:61772328

  3. 需求变更\系统演化环境下的特征化需求模型的代码综合方法,国家自然科学基金项目,项目编号:61603242

  4. 基于鞅论的脉冲随机神经网络协同分析及自适应同步的研究,国家自然科学基金项目,项目编号:61503238

  5. 基于SXM模型的Web软件测试理论与方法,国家自然科学基金项目,项目编号:61262010


【横向项目】

  1. 基于计算机视觉与激光融合的目标检测算法开发,上海振华重工电气有限公司。

  2. 天长市天翔集团有限公司SmartOA项目(一期),天长市天翔集团有限公司。

  3. 外高桥集团信息化发展规划,上海外高桥集团股份有限公司。


【论文发表】

  1. A lightweight RGB superposition effect adjustment network for low-light image enhancement and denoising. Pei-Dong Chen, Juan Zhang*, Yong-Bin Gao, Zhi-Jun Fang, Jenq-Neng Hwang[J]. Engineering Applications of Artificial Intelligence, Vol. 127, Part A, 2024, 107234.

  2. Jiaolong Yu, Juan Zhang*, Yongbin Gao. MACFNet: multi-attention complementary fusion network for image denoising[J]. Applied Intelligence, 2023, Vol. 53(13): 16747-16761. IF5.3中科院二区)

  3. ChenYu Zheng, Juan Zhang*, Jenq-Neng Hwang, Bo Huang. Double-Branch Dehazing Network based on Self-Calibrated Attentional Convolution[J]. Knowledge-Based Systems, 2022, 240:108148. IF8.8中科院一区)

  4. Jiahao Zhang, Juan Zhang*, Xing Wu, Zhicai Shi, Jenq-Neng Hwang. CFMFN: Coarse-to-Fine Multi-scale Fusion Network for SingleImage Deraining[J]. Journal of Electronic Imaging, 2022, Vol. 31(4). IF1.1中科院四区)

  5. Juan Zhang, Xiaoqi Lang, Bo Huang, Xiaoyan Jiang.VAE-CoGAN: Unpaired Image-to-Image Translation for Low-Level VisionSignal Image and Video Processing. 2022/7/11.IF2.3中科院四区)

  6. Wenbin Guo, Juan Zhang. Semi-Supervised Learning for Raindrop Removal on a Single Image [J]. Journal of Intelligent & Fuzzy Systems, 2022, 42:4041–4049IF2.0中科院四区)

  7. KunYang, Juan Zhang*, Zixuan Ding. Multiple Patch-Aware Network for Faster Real-World Image Dehazing.IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP), 2022.

  8. 郭梦琰, 张娟, 刘巧红,蔡立志. 基于循环生成对抗网络的图像去雾算法[J]. 计算机工程, 2022,(3): (048-003).

  9. YanZhang, Juan Zhang*, BoHuang, ZhijunFang. Single-image deraining via a Recurrent Memory Unit Network[J].Knowledge-Based Systems, 2021, 218: 106832. IF8.8中科院一区)

  10. 张焱, 张娟, 方志军. 基于通道注意力和门控循环单元的图像去雨算法[J]. 计算机应用研究, 2021,38(8):2505-2509.

  11. Mengyan Guo, Bo Huang, Juan Zhang*, Feng Wang, Yan Zhang, Zhijun Fang, DFBDehazeNet: an end-to-end dense feedback network[J]. Journal of Electronic Imaging, 2021,30(3). IF1.1中科院四区)

  12. Feng Wang, Lizhi Cai, Juan Zhang*, Yan Zhang, Mengyan Guo, Zhijun Fang. Joint blind image deblurring and super-resolutionvia double-branch projection feedback network[J]. Journal of Electronic Imaging, 2021, 30(2). IF1.1中科院四区)

  13. Qiu Xiong, Zhang Juan*, Zhu Wumingrui, Zhang Shuqi, Kong Lihong. Weight-Edge Convolution Neural Network for Point Clouds Learning[J]. Wuhan University Journal of Natural Sciences 2021, Vol.26, No.2.

  14. 杨坤,张娟,方志军. 基于多补丁和多尺度层级聚合网络的快速非均匀图像去雾[J]. 计算机科学, 2021, 48(11): 250-257.

  15. 詹雁;张娟;金昌基.联合语义感知与域适应方法的单目深度估计[J].传感器与微系统.2021-05-12.

  16. 张焱;张娟;方志军.基于通道注意力和门控循环单元的图像去雨算法[J]. 计算机应用研究, 2021-02-01.

  17. 杨坤;张娟;方志军.基于多补丁和多尺度层级聚合网络的快速非均匀图像去雾[J]. 计算机科学,2021-11-15.

  18. 王峰;蔡立志;张娟.基于双分支融合的反馈迭代金字塔去模糊和超分辨率算法[J]. 计算机应用研究, 2021-11-05.

  19. Yan Zhang, Juan Zhang*, Feng Wang, Mengyan Guo, Lizhi Cai, and Qiaohong Liu.Image Deraining Using Multi-scale Aggregated Generator Network[J]. Journal of Electronic Imaging, 2020,29(6),063003. IF1.1中科院四区)

  20. 张焱;郭梦琰;王峰.基于循环卷积神经网络的模块化文字识别[J].智能计算机与应用,2020-10-01. 已认领

  21. 詹雁, 张娟.一种结构感知损失的域适应深度估计方法[J]. 电子科技, 2020-01-06.已认领

  22. 李明东, 张娟, 伍世虔. 基于RANSAC变换的车牌图像去模糊算法[J].传感器与微系统,2020-01-21.

  23. 许明;张娟;方志军.自适应道路模型的非结构化道路检测算法[J]. 传感器与微系统, 2020-01-20.

  24. JingmingZhao, JuanZhang*, ZhiLi, Jenq-NengHwang, YongbinGao, ZhijunFang, XiaoyanJiang, BoHuang. DD-CycleGAN: Unpaired image dehazing via Double-Discriminator Cycle-Consistent Generative Adversarial Network[J]. Engineering Applications of Artificial Intelligence, 2019, 82:263-271. IF8.2中科院二区)

  25. Yucheng Wang, Juan Zhang*, Hao Jiang, Zhijun Fang, Road detection using cycle-consistent adversarial networks[J]. Journal of Electronic Imaging, 2019,28(5), 053021. IF1.1中科院四区)

  26. ZhiLi, JuanZhang*, ZhijunFang, BoHuang, XiaoyanJiang, YongbinGao, Jenq-NengHwang. Single Image Snow Removal via Composition Generative Adversarial Networks[J]. IEEE Access, 2019,7:25016-25025. IF3.9中科院三区)

  27. 李智, 张娟, 方志军. 基于循环生成对抗网络的道路场景语义分割[J]. 武汉大学学报:理学版, 2019(3):303-308.

  28. Renyue Dai, Yongbin Gao*, Zhijun Fang, Xiaoyan Jiang, Anjie Wang, Juan Zhang, Cengsi Zhong. Unsupervised learning of depth estimation based on attention model and global pose optimization[J]. Signal Processing: Image Communication, vol. 78, pp. 284-292, 2019. (SCI, IF3.256)

  29. Xiaoyan Jiang, Zhijun Fang, Neal N. Xiong, Yongbin Gao, Bo Huang, Juan Zhang, Lei Yu, Patrick Harrington. Data Fusion-based Multi-object Tracking for Unconstrained Visual Sensor Networks. 2018. IEEE ACCESS(4): p. 3233-3246.000429142100001

  30. Mindong Li, Juan Zhang*, Zhijun Fang. License Plate Character Recognition Method Based on Combination Feature and BP Network.2017 International Conference on Smart and Sustainable City.  (EI:20182105221079)

  31. Xiang Wang, Juan Zhang*, Zhijun Fang. Unstructured road detection based on contour selection. 2017 International Conference on Smart and Sustainable City. (EI:20182105221080)

  32. Ming Xu, Juan Zhang*, Zhijun Fang. Research on Unstructured Road Detection Algorithm Based on an Improved Morphological Operations. 2017 International Conference on Smart and Sustainable City. (EI:20182105221078)

  33. Xiangyang Wang, YusuJin, Zhi Liu, Yadong Zhao,Xiaoqiang Zhu, and Juan Zhang. Multi-scale Deep Residual Networksfor Fine-Grained Image Classificationfor Fine-Grained Image Classification, International Forum of Digital TV and Wireless Multimedia Communication. Springer, Singapore, 2016: 205-217.

  34. Po-Han Wu, Chih-Wei Huang, Jenq-Neng Hwang, Jae-Young Pyun, Juan Zhang. Visual Quality Driven Resource Allocation for Real-Time Surveillance Video Uplinking over OFDMA-based Wireless Networks. IEEE Transaction on Vehicular Technology, 2015.64(7): p. 3233 - 3246.WOS:000358239500036IF6.8中科院二区)

  35. Zhijun Fang, Juan Zhang, Wanggen Wan, Yuming Fang. An Effective Video Saliency Detection Model Based on Human Visual Acuity and Spatiotemporal Cues in Cloud Systems. Journal of Internet Technology, 2014. Vol. 15 No. 5: 835-840. (EI:20144700235449, WOS:000342605500014) (IF1.005)

  36. Juan Zhang, LizhiCai, Weiqin Tong, Wenbin Huang, Jenq-Neng Hwang. Reusing Test Case Model Based on Function Point. Journal of DongHua University, 2014. vol. 31, No. 4441-446.(EI: 20150200409208)

  37. 张娟, 张习民, 万旺根, 方志军.利用显著性点云模型的质量客观评价.应用科学学报, 2014. 32(05): 441-446.

  38. Juan Zhang, Wanggen Wan, Wenbin Huang, Jenq-Neng Hwang. A Subjective Quality Evaluation For 3D Point Cloud Models. 2014 International Conference on Audio, Language and Image Processing, Shanghai China, 2014, July.(EI: 20150700517967)

  39. Jing Wang, Juan Zhang, Qingtong Xu. Research on 3D Laser Scanning Technology Basedon Point Cloud Data Acquisition.2014 International Conference on Audio, Language and Image Processing, Shanghai China, 2014, July.(EI:20150700517521)

  40. Xiaoqiang Zhu, Junli Chen, Juan Zhang, Wanggen Wan.A two-phase approximation of cylindrical branching models. 2014 International Conference on Audio, Language and Image Processing, Shanghai China, 2014, July. (EI20150700517971)

  41. 张习民, 余小清, 万旺根, 张娟.压缩感知点云数据压缩, 应用科学学报, 2014. 32(05): 458-462.

  42. 张娟, 童维勤, 蔡立志.基于复用簇的测试用例库度量模型.小型微型计算机系统, 2013. 34(005): 1035-1041.

  43. 张娟, 童维勤, 蔡立志.基于Z规约的可复用测试用例库形式化描述.计算机工程, 2012. 38(16)44-48.

  44. Juan Zhang, Tong Weiqing, CaiLizhi. An Evaluation Model in Software Testing Based on AHP. 11th IEEE/ACIS International Conference on Computer and Information Science, 2012, p 601-604. ( EI:20123015276265)

  45. LizhiCai, Juan Zhang, Zhenyu Liu. A CPN-based Software Testing Approach, Journal of Software, vol.6, No.3, p 468-474, 2011. ( EI:20111313877743)

  46. ShaojieGuo, Weiqin Tong, Juan Zhang, Zongheng Liu. An Application of Ontology to Test Case Reuse, 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, 2011, p 775-778. ( EI: 20114114423455)

  47.  袁松, 杨根兴, 张娟.基于层次分析法的测试用例可复用性度量研究.计算机应用与软件, 2011. 28(9): p. 60-63.

  48. 刘小齐, 杨根兴, 蔡立志, 张娟. 基于复用行为的测试用例本体描述和检索. 计算机应用与软件, 2011. 28(10): p. 65-68.

  49. Juan Zhang, LizhiCai, WeiqingTong, SongYuan, YingLi. Test Case Reusability Metrics Model. 2010 International Conference on Computer Technology and Development, 2010, p 294-298.( EI:20105213534907)

  50. LizhiCai, Juan Zhang, Zhenyu Liu. Generating Test Cases Using Colored Petri Net. The 2nd International Symposium on Information Engineering and Electronic Commerce, p 114-118, 2010. ( EI: 20103613209985)

  51. Juan Zhang, LizhiCai, Weiqin Tong, Zhenyu Liu, Ying Li. A Dynamic Metric Method for Test Case Reuse Based on Bayesian Network. 2009 International Conference on Computational Intelligence and Software Engineering, p. 1-5.(EI:20101212799435)

  52. LizhiCai, Zhenyu Liu, Juan Zhang, Weiqin Tong, Genxing Yang. Evaluating Software Maintainability Using Fuzzy Entropy Theory. The 9th IEEE/ACIS International Conference on Computer and Information ScienceICIS 2010, p 737-742. ( EI:20104813422256)

  53. LizhiCai, Weiqin Tong, Zhenyu Liu, Juan Zhang. Test Case Reuse Based on Ontology. The 15th IEEE Pacific Rim International Symposium on Dependable Computing(2009 PRDC), p 103-108.

( EI: 20101012758187)