人员

教师

张建国    教授

电子邮箱:

zhangjg_AT_sustech.edu.cn

办公室:

南方科技大学创园10栋404室

研究方向:

计算机视觉、医学图像及信息处理、机器学习、人工智能等

教育背景

1999-2002中科院北京自动化所模式识别国家重点实验室,博士

1996-1999山东工业大学(现山东大学),硕士

1992-1996山东工业大学(现山东大学),学士


工作经历

2019 –至今南方科技大学计算机系教授

2015-2019 英国邓迪大学科学与工程学院计算机系Reader,计算机系国际合作主任

2010-2015 英国邓迪大学科学与工程学院计算机系高级讲师

2007-2010 英国贝尔法斯特女王大学计算机系讲师

2005-2007 英国伦敦大学玛利亚女王学院计算机系,博士后研究员

2003-2005 法国国家信息与自动化研究院(INRIA),博士后研究员

2002-2003 新加坡南洋理工大学,博士后研究员


荣誉与奖项

国家特聘专家

2010 IEEE高级会员

2017年,在加拿大魁北克举办的国际基于核磁共振的脑部白质高亮区域分割竞赛中 (MICCAI 2017- Brain WMH Segmentation Challenge) 获冠军

2016年和UCL一起获Olea Medical- Olea Innovators contest prize

2015 年, 在德国慕尼黑,由 MICCAI15 举办的内窥镜视觉竞赛中的两个项目上取得第一名的成绩(Endoscopic Vision Challenge on sub challenges of Polyp Localization and Early Barret’s Cancer detection), MICCAI15, Munich

2014 年在瑞典斯坦哥尔摩举办的国际医学图像识别竞赛(“Performance Evaluation of Indirect Immunofluorescence Image Analysis Systems”–ICPR 2014)中取得优异成绩,所有项目(cell and specimen classification)上均获第一

2014 年英国国际医学图像理解和分析大会的最佳癌症类论文奖

2014 年哈佛大学举办的脑部癌症病理图片分割竞赛中取得优异成绩。(Brain Tumour Digital Pathology Challenge –MICCAI2014- 医学图像处理顶级会议),算法性能第二

2008 年国际机器视觉和图像处理大会的最佳论文奖。(International Machine Vision and Image Processing Conference 2008

在 2006 年由欧洲 PASCAL 主办的国际视觉目标物体的分类竞赛(PASCAL Visual Object Classification Challenge)中所有 10 个项目上取得优异成绩,在多个项目上第一

在 2005 年在第一届国际视觉目标物体分类竞赛(PASCAL Visual Object Classification Challenge)中所有 8 个项目上取得优异成绩,在多个项目上第一

2002 年获中科院院长奖学金优秀奖

 


代表文章

1. Hugo J. Kuijf, & Jianguo Zhang, et al, Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities: Results of the WMH Segmentation Challenge, IEEE Transactions on Medical Imaging, 2019.( Summary of the Contest, and Winning method for the International challenge on brain White Matter Hyperintensities (WMH) segmentation, MICCAI 2017. See our NeuroImage paper for the details of the method)

2. Hu JF, Zheng WS, Ma LY, Wang G, Lai JH, and Zhang J, Early Action Prediction by Soft Regression, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 . 

3. Hongwei Li, Gongfa Jiang, Ruixuan Wang, Jianguo Zhang, Zhaolei Wang, Wei-Shi Zheng, BjoernMenze, Fully Convolutional Network Ensembles for White Matter Hyperintensities Segmentation in MR Images, NeuroImage, 2018 (Winning method for the International challenge on brain White Matter Hyperintensities (WMH) segmentation, MICCAI-2017).

4. S. Bano, T. Suveges, J Zhang, S McKenna (2018), Multimodal, Egocentric Analysis of Focused Interactions, IEEE Access, 2018.

5. Sotirios Bisdas, Haocheng Shen, Steffi Thust, VasileiosKatsaros, George Stranjalis, Christos Boskos, Sebastian Brandner, and Jianguo Zhang, (2018) Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study, Scientific Report, Nature (Winning Methods for the Olea Innovators Contest prize for technology transfer).

6. Yan Li, Junge Zhang, Jianguo Zhang, Kaiqi Huang, Mixed Supervised Object Detection with Robust Objectness Transfer, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.

7. Daniel R Morales, Rob Flynn, Jianguo Zhang, Emmanuel Trucco, Jennifer K Quint, Kris Zutis (2018) External validation of ADO, DOSE, COTE and CODEX at predicting death in primary care patients with COPD using standard and machine learning approaches, Respiratory Medicine, Vol. 138, pp.150-155.

8. Siyamalan Manivannan, Wenqi Li, Jianguo Zhang, Emanuele Trucco, Stephen McKenna (2017), Structure Prediction for Gland Segmentation with Hand-Crafted and Deep Convolutional Features,  IEEE Trans. on Medical Imaging, 2017, DOI: 10.1109/TMI.2017.2750210. 

9. Shaofan Lai, Weishi Zheng, Jiangfang Hu, Jianguo Zhang, Global-Local Temporal Saliency Action Prediction,  IEEE Transactions on Image Processing, 2017.

10. J. Hu, W. Zheng, J. Lai,  J Zhang, Jointly Learning Heterogeneous Features for RGB-D Activity Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol.39 (11), 2017, pp.2186-2200.

11. Siyamalan Manivannan, Wenqi Li, Shazia Akbar, Ruixuan Wang, Jianguo Zhang and Stephen J. McKenna An Automated Pattern Recognition System for Classifying Indirect Immunofluorescence Images of HEp-2 Cells and Specimens, Pattern Recognition, Volume 51, March 2016, p. 12-26 (Winning Methods for ICPR I3A Contest).

12. Wenqi Li, Maria Coats, Jianguo Zhang and Stephen McKenna (2015), Discriminating Dysplasia: optical tomographic texture analysis of colorectal polyps, Medical Image Analysis.

13. Xiaojuan Wang, Wei-Shi Zheng, Xiang Li, and Jianguo Zhang, Cross-scenario Transfer Person Re-identification, IEEE Trans Circuits and Systems for Video Technology.

 

Refereed Conference Publications (selected) 

1. Hongwei Li, Johannes C Paetzold, AnjanySekuboyina, Florian Kofler, Jianguo Zhang, Jan S Kirschke, BenediktWiestler, and BjoernMenze, DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis, MICCAI 2019.

2. Xionghui Wang, Jian-Fang Hu, Jianhuang Lai, Jianguo Zhang and Wei-Shi Zheng, Progressive Teacher-student Learning for Early Action Prediction, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019

3. Jiaxin Zhuang, JiabinCai, Ruixuan Wang, Jianguo Zhang, Weishi Zheng CARE: Class Attention to Regions of Lesion for Classification on Imbalanced DataMedical Imaging with Deep Learning Conference (MIDL -- in par with MICCAI) 2019 

4. Jian-Fang Hu, Wei Shi Zheng, Jiahui Pan, Jian-Huang Lai, Jianguo Zhang (2018), Deep Bilinear Learning for RGB-D Action Recognition, European Conference on Computer Vision (ECCV).

5. Yan Li, Junge Zhang, jianguo Zhang, Kaiqi Huang, Discriminative Learning of Latent Features for Zero-Shot Recognition, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

6. Hongwei Li, Jianguo Zhang, Mark Meuhlau, Jan KirschkeandBjoernMenze (2018), “Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation”, BrainLesin International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI).

7. Haocheng Shen, Ruixuan Wang, Jianguo Zhang, Stephen McKenna (2017), Boundary-aware Fully Convolutional Network for Brain Tumor Segmentation, MICCAI, 2017 (top conference in medical image analysis) https://doi.org/10.1007/978-3-319-66185-8_49

8. Weihua Chen, Xiaotang Chen, Jianguo Zhang, and Kaiqi Huang (2017), Beyond triplet loss: a deep quadruplet network for person re-identification, IEEE Conference on Computer Vision and Pattern Recognition (CVPR).


其他信息

Associate Editor of IEEE Trans. On Multimedia (2019 – present)

Associate Editor of IET Computer Vision (2017 - present)

Associate Editor of EURASIP Advances in Signal Processing (2016-present)

Gest Editor of Pattern Recognition (2012)

Area Chair of BMVC (2010 –present)

PCs/reviews for ICCV, CVPR, ECCV, AAAI, IEEE PAMI, IJCV etc

Founding Chair and Organizer of VECTaR 2013 2012, 2011, 2010, 2009 (in conjunction with ICCV 2013, ECCV12, ICCV11 etc),