导师代码： 10883
导师姓名： 文泉
性别： 男
特称：

职称： 副教授
学位： 工学博士学位
属性： 专职
电子邮件： qwuta@163.com

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学术经历： 研究方向是机器学习，人工智能，模式识别，数据挖掘，计算机图像和视频处理。以第一作者在国际顶尖会议和杂志发表SCI/EI检索的文章40余篇。担任了多个一流国际刊物和会议的审稿人，其中包括：IEEE Transaction on Medical Image Processing, IET Image Processing, International Journal of Image Processing, International Journal of Data Mining and Bioinformatics, IEEE International Conference on Pattern Recognition, IASTED International Conference on Visualization, Imaging, and Image Processing等，以及国际会议IADIS International Conference on Computer Graphics, Visualization, Computer Vision And Image Processing ，ISVC: Special Track on Low-Level Color Image Processing等的大会程序委员会委员。现担任国际期刊“International Journal of Biometrics and Bioinformatics (IJBB)”和“International Journal of Intelligent Information Processing (IJIIP)”的编委。曾参与了美国National Science Foundation，National Institutes of Health，Department of Energy 等资助的多项顶尖科研项目。长期同美国、加拿大、澳大利亚的研究人员在生物医学图像处理上保持紧密合作。入选电子科技大学计算机学院杰出后备人选资助计划，荣获年度“科技人物”的称号。现以第一负责人主持国家自然科学基金资助项目2项，校内资助项目3项。

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个人简介： 本科毕业于四川大学原子核科学与技术研究所自动控制专业,硕士毕业于四川大学计算中心计算机应用专业，获美国德克萨斯大学阿灵顿分校计算机科学与工程博士学位，在美国伯克利国家实验室生命科学部从事博士后研究，现担任电子科技大学计算机科学与工程学院副教授，并担任多个国际一流学术期刊和会议的编委和审稿人。主要研究兴趣为机器学习，人工智能，模式识别，计算机图像和视频处理的理论及应用。

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科研项目： 第一负责人主持国家自然科学基金资助项目2项，校内资助项目3项。

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研究成果： 论文发表:共41篇。SCI/EI检索40篇
期刊 (Journal)
1)H. Chang, Q. Wen, and B. Parvin, “Coupled segmentation of nuclear and membrane-bound macromolecules through voting and multiphase level set,” Pattern Recognition, vol. 48, no. 2, 2015.(SCI-E)
(2)M. E. Celebi,S. Hwang, and Q. Wen “An effective real-time color quantization method based on divisive hierarchical clustering,” Journal of Real-Time Image Processing, vol. 10, no. 3, 2015. (SCI-E)
(3)M. E. Celebi, S. Hwang, and Q. Wen, “Colour quantisation using the adaptive distributing units algorithm,” The Imaging Science Journal, vol. 62, no. 2, pp. 80-91, Feb. 2014. (SCI-E)
(4)M. E. Celebi, S. Hwang, and Q. Wen, “Colour quantisation using the adaptive distributing units algorithm,” The Imaging Science Journal, vol. 62, no. 2, pp. 80-91, Feb. 2014. (SCI-E)
(5)M. E. Celebi, Q. Wen, S. Hwang, H. Iyatomi, and G. Schaefer, “Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods,” Skin Research and Technology, vol. 19, no. 1, pp. e252–e258, 2013. (SCI-E)
(6)M. E.Celebi, Q. Wen, and S. Hwang, “An effective real-time color quantization method based on divisive hierarchical clustering,” Special Issue, Journal of Real-Time Image Processing, Nov. 2012, DOI 10.1007/s11554-012-0291-4. (SCI-E)
(7)Q. Wen and M. E. Celebi, “Hard Versus Fuzzy C-Means Clustering for Color Quantization,” EURASIP Journal on Advances in Signal Processing, vol. 2011, no. 1, p. 118, 25 Nov., 2011. (SCI-E)
(8)Q. Wen, J. Gao, and K. Luby-Phelps, “Tracking multiple interacting subcellular structure by sequential Monte Carlo method,” International Journal of Data Mining and Bioinformatics, vol. 3, no. 3, pp. 314-322, 2009. (SCI-E)
(9)S. Gopinath, Q. Wen, N. Thakoor, K. luby Phelps, and J. Gao, “A statistical approach for intensity loss compensation of confocal microscopy images,” Journal of Microscopy, vol. 230, pp. 143-159, 2008. (SCI-E)
(10)K. Nojima, S. Brown, C. A. J. Janis, G. Arbique, T. Abulezz, J. Gao, Q. Wen, K. Kurihara, and R. Rohrich, “Defining vascular supply and territory of thinned perforator flaps: Part II superior gluteal artery perforator flap,” Plastic & Reconstructive Surgery, vol. 118, no. 6, pp. 1338-1348, Nov 2006. (SCI-E)
专著章节 (Book Chapter)
(11)M. Emre Celebi, QuanWen, Sae Hwang, and Gerald Schaefer, “Color Quantization of Dermoscopy Images Using the K-Means Clustering Algorithm,” Color Medical Image Analysis, Springer, pp. 87-107, 2013.
国际会议 (Conference)
(12)Q. Wen, D. Ming, J. Chen, and W. Liu, “A superpixel based post-processing approach for segmenting dermoscopy images,” IEEE International Conference on Advanced Computational Intelligence (ICACI), pp. 155-158, Hangzhou, China, Oct. 19-21, 2013, poster. (EI)
(13)Q. Wen, D. Ming, and J. Chen, “A novel fusion approach for segmenting dermoscopy image based on region consistency,” IEEE International Conference on Computational Problem-Solving (ICCP), pp. 267-270, Jiuzhai Valley, China, Oct. 26-28, 2013, poster. (EI)
(14)Q. Wen, J. Chen, and W. Liu, “Quantitative analysis on mobility behaviors of fluorescent marker proteins using the graph model,” IEEE International Congress on Image and Signal Processing (CISP), pp. 647-651, Hangzhou, China, Dec. 16-18, 2013, poster. (EI)
(15)Q. Wen, J. Chen, and W. Liu, “Biologically inspired classification of microvessel histopathology via sparse coding,” IEEE International Conference on Advanced Computational Intelligence (ICACI), pp. 114-118, Hangzhou, China, Oct. 19-21, 2013, poster. (EI)
(16)Q. Wen, J. Chen, and W. Liu, “A predictive coding approach on microvessel identification via single-opponent signals,” IEEE International Congress on Image and Signal Processing (CISP), pp. 1530-1534, Hangzhou, China, Dec. 16-18, 2013, poster. (EI)
(17)D. Ming, Q. Wen, J. Chen, and W. Liu, “A generalized fusion approach for segmenting dermoscopy images using markov random field,” IEEE International Congress on Image and Signal Processing (CISP), pp. 508-513, Hangzhou, China, Dec. 16-18, 2013, poster. (EI)
(18)M.E. Celebi and Q. Wen, “Variance-cut: a fast color quantization method based on hierarchical clustering,” in Proceedings of the 10th International Conference on Electronics, Computer and Computation (ICECCO 2013), pp. 103-106, Ankara, Turkey, Nov. 7-9, 2013, Oral. (EI)
(19)M. Mete, J. Chen, Q. Wen, and X. Liu, “Color region annotation for microvessel density Estimation,” 2012 International Conference on Wavelet Active Media Technology and Information Processing, 17-19 December 2012, Chengdu China, pp. 145-148. (EI)
(20)J. Chen, Q. Wen, Z. Pang, and M. Mete, “An Effective Approach Towards Color Image Segmentation for Micro-Vessel Detection,” 2012 3rd International Conference on Computational Problem-Solving, 19-21 October 2012, Leshan China, pp. 59-63. (EI)
(21)J. Chen, Q. Wen, C. Zhuo, and M. Mete, “Pose Recognition of Giant Pandas Based on Gradient Shapes”, 2012 3rd International Conference on Computational Problem-Solving, 19-21 October 2012, Leshan China, pp. 358-362. (EI)
(22)Q. Wen, W. Qu, J. Chen, and M. Mete, “A Novel Method for Counting Subcellular Structures Labeled by Green Fluorescent Protein,” 2012 3rd International Conference on Computation Problem-Solving, 19-21 October 2012, Leshan China, pp. 500-503. (EI)
(23)Q. Wen, W. M. Qu, J. Chen, and M. Mete “A Novel Method for Counting Subcellular Structures Labeled by Green Fluorescent” 2012International Conference on Computational Problem-solving (ICCP2012), Oct. 19-21, 2012, Chengdu and Leshan, China，pp. 500-503. (EI)
(24)J. Chen, Q. Wen, C. Zhuo, and M. Mete, “Extraction of Color Entropy Sequence for Micro-vessel Detection in Virtual Slide,” 2012 5th International Congress on Image and Signal Processing, 16-18 October 2012, Chongqing, China, pp. 1028-1032. (EI)
(25)J. Chen, Q. Wen, W. Qu, and M. Mete, “Panda Facial Region Detection Based on Topology Modelling,” 2012 5th International Congress on Image and Signal Processing, 16-18 October 2012, Chongqing, China, pp. 1072-1076. (EI)
(26)J. Chen, Q. Wen, C. Zhuo, and M. Mete, “Automatic Head Detection for Passenger Flow Analysis in Bus Surveillance Videos,” 2012 5th International Congress on Image and Signal Processing, 16-18 October 2012, Chongqing, China, pp. 164-168. (EI)
(27)J. Chen, Q. Wen, C. Zhuo, and M. Mete, “A Novel Approach Towards Head Detection of Giant Pandas in the Free-Range Environment,” 2012 5th International Congress on Image and Signal Processing, 16-18 October 2012, Chongqing, China, pp. 971-975. (EI)
(28)M. E. Celebi, Q. Wen, G. Schaefer, and H. Zhou, “Batch Neural Gas with Deterministic Initialization for Color Quantization,” in 6 th Proc. Int. Conf. on Computer Vision and Graphics (ICCVG 2012), L. Bolc et al. (eds.), “Computer Vision and Graphics”, Lecture Notes in Computer Science, LNCS Vol. 7594, Springer, Sep. 24–26, 2012, pp. 48-54. (EI)
(29)M. E. Celebi, Q. Wen, and J. Chen, "Color Quantization Using C-Means Clustering Algorithms," in Proceedings of 18th IEEE International Conference on Image Processing (ICIP 2011), Brussels, Belgium, Sep. 11-14, 2011, pp. 1729–1732. (EI)
(30)Q. Wen, M. E. Celebi, and G. Schaefer, “A Comparative Study of K-Means and Fuzzy C-Means for Color Reduction,” in proceedings of 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV’11), Oral, Las Vegas, Nevada, US, July 18-21, 2011. (Oral) (EI)
(31)Q. Wen, J. Gao, and K. Luby-Phelps, “Tracking Variable Number of Multiple Subcellular Structures in 3D,” in proceedings of IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC2009), Minneapolis, MN, Sep. 2-6, pp. 1465-1468. (EI)
(32)Q. Wen, H. Chang, and B. Parvin, “Delaunay triangulation approach for segmenting clumps of nuclei”, in proceedings of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, (ISBI '09). June 2009, pp. 9-12, Boston, MA.(EI)
(33)Q. Wen, J. Gao, and K. Luby-Phelps, “Multiple interacting subcellular structure tracking by sequential Monte Carlo method,” in proceedings of IEEE International Conference on Bioinformatics and Medicine (BIBM2007), Silicon Valley, Nov. 2007, pp. 437-442. (EI)
(34)Q. Wen and J. Gao, “Tracking interacting subcellular structures by sequential Monte Carlo method,” in proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBC2007), Lyon, France, 22-26 Aug. 2007, pp. 4185-4188. (EI)
(35)Q. Wen, J. Gao, and K. Luby-Phelps, “Markov chain Monte Carlo data association for merge and split detection in tracking protein clusters,” in proceedings of IEEE International Conference on Pattern Recognition (ICPR2006) (15% oral acceptance rate), vol. 1, Hong Kong, 2006, pp. 1030-1033. (EI)
(36)N. Thakoor, S. Jung, Q. Wen, and J. Gao, “Occlusion resistant shape classifier based on warped optimal path matching,” in proceedings of IEEE International Conference on Pattern Recognition (ICPR 2006) ) (15% oral acceptance rate), Hong Kong, Aug. 2006, pp. 60-63. (EI)
(37)Q. Wen, J. Gao, and K. Luby-Phelps, “Feature selection, matching, and evaluation for subcellular structure tracking,” in proceedings of IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC 2006), NYC, Aug. 2006, pp. 3013-3016. (EI)
(38)Q. Wen, Jean Gao, and K. Luby-Phelps, “Region-based tracking of protein compounds,” in proceedings of IEEE International Symposium on Biomedical Imaging (ISBI 2006), VA, April 2006. pp.574-577. (EI)
(39)Q. Wen, J. Gao, A. Kosaka, H. Iwaki, H, K. Luby-Phelps, and D. Mundy, “A particle filter framework using optimal importance function for protein molecules tracking,” in proceedings of IEEE International Conference on Image Processing (ICIP 2005), Sept. 2005, Vol. 1, pp.1161- 1164. (EI)
(40)Q. Wen and J. Gao, “Shape-based 3D vascular tree extraction for perforator flaps,” in proceedings of SPIE on Medical Imaging, vol. 5747, 2005, pp. 1855-1863. (EI)
(41)J. Gao and Q. Wen, “Automatic 3D vascular tree construction of perforator flaps for plastic surgery planning,” in proceedings of IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC 2004), San Francisco, CA. Sep. 2004, pp.3424-3427. (EI)

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专业研究方向： 专业名称 研究方向 招生类别
081200计算机科学与技术 02机器智能与模式识别 硕士
081200计算机科学与技术 03数字媒体技术 硕士
081200计算机科学与技术 06云计算与大数据处理 硕士

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