姓名：陈娟 专业技术职务：副教授
联系方式：
邮箱：chenjuan@uestc.edu.cn
系别：计算机工程与应用系

联系方式 邮箱 chenjuan@uestc.edu.cn
专业技术职务_详情页 副教授


个人背景 2001年-2005年:西南师范大学,本科;
2005年-2006年:西南师范大学,硕士;
2006年-2009年:英国布拉德福德大学,博士;
2009年-2012年:电子科技大学,讲师;
2012年-至今:电子科技大学,副教授;

研究方向 人工智能、机器学习、模式识别、图像和视频处理

讲授课程
本科：《数字逻辑（双语）》、《数字逻辑综合实验》、《数字逻辑设计（全英文）》
研究生：《统计学习理论及应用》

研究成果 研究项目：
1.面向新工科的《人工智能》线上、线下混合式教学改革，教育部-百度产学合作项目，2020.01-2020.12，主持；
2.面向新工科的《人工智能》课程教学改革，教育部-华为产学合作项目，2019.01-2019.12，主研；
3.《人工智能》示范课程建设，教育部-北京海云捷迅产学合作项目，2020.01-2020.12，主研；
4. Fast Microvessel Detection in Virtual Slides of Solid Tumors，国家自然科学基金（国际合作项目），2012.01-2012.12，承接；
5.动态光场的高效编码与高质量重建，国家自然科学基金重点国际（地区）合作研究项目，2021.01-2025.12，主研；
6.基于本体的认知推理模型及其应用研究，国家自然科学基金（青年科学基金项目），2013.01-2015.12，主研；
7.基于身份加密的新型设计与形式化分析，国家自然科学基金（青年科学基金项目），2012.01-2014.12；主研；
8.面向云计算的混合诊断与自修复理论研究，国家自然科学基金（面上项目），2012.01-2015.12，主研；
9.可学习的任意维细胞神经网络及其新应用研究，国家自然科学基金（青年科学基金项目），2012.01-2015.12，主研；
10.基于荧光显微镜图像序列的亚细胞结构运动定量分析的关键技术研究，国家自然科学基金（面上项目），2011.01-2013.12，主研；
11.基于深度学习与SVM的乳腺结节超声造影的辅助诊断，中央高校基本科研业务费项目，2017.01-2018.12，主持；
12.基于语义特征提取的视频盗版检测，中央高校基本科研业务费项目，2011.01-2012.12，主持；
13.《数字逻辑概论（全英文教材）》，电子科技大学2019年规划教材项目，2019.05-2020.11，主持；
14.《统计学习原理及应用》研究生精品课程配套教材，电子科技大学2020年第三批研究生精品课程及配套教材建设项目，2020.07-2022.03，主研；
15.挑战性学习课程《统计学习理论及应用》，电子科技大学2019年度挑战性学习课程建设项目（重点项目），2019.07-2020.03，主持；
16.挑战性学习课程《人工智能应用与挑战》，电子科技大学2019年度挑战性学习课程建设项目，2019.07-2020.03，主研；
17.《人工智能》，电子科技大学大规模在线开放课程建设项目（第四批），2019.08-2020.08，主研；
18.《统计学习理论及应用》研究生精品课程，电子科技大学2019年第一批研究生精品课程建设项目，2019.04-2020.12，主研；
19.基于OpenCV平台的图像处理编程实验，电子科技大学新实验建设专项，2014.12-2015.04，主持；
20.可视化编程实验，电子科技大学新实验建设专项，2013.07-2013.11，主持；
21.多媒体技术综合实验，电子科技大学新实验建设专项，2011.11-2012.03，主持；
22.实验课程答题测评系统，电子科技大学实验创新基金项目，2010.01-2010.06，主持；

论文列表：
[1] J. Chen, S. Zhou, Z. Kang and Q. Wen, “Locality-Constrained Group Lasso Coding for Microvessel Image Classification,” Pattern Recognition Letters, vol. 130, pp. 132-138, 2020.
[2] Z. Wu, R. Xiamixiding, A. Sajjanhar, J. Chen and Q. Wen, “Image Appearance-Based Facial Expression Recognition,” International Journal of Image and Graphics, vol. 18, no. 02, 2018.
[3] J. Chen, J. Ren and J. Jiang, “Modelling of Content-Aware Indicators for Effective Determination of Shot Boundaries in Compressed MPEG Videos,” Multimedia Tools and Applications, Springer, vol. 54, no. 2, pp.219-239, 2011.
[4] J. Ren, J. Jiang, J. Chen and S.S. Ipson “Extracting Objects and Events from MPEG Videos for Highlight-Based Indexing and Retrieval,” Journal of Multimedia, vol. 5, no. 2, pp. 95-103, 2010.
[5] J. Ren, J. Jiang and J. Chen, “Shot Boundary Detection in MPEG Videos using Local and Global Indicators,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 8, pp. 1234-1238, 2009.
[6] J. Jiang, Z. Li, G. Xiao and J. Chen, “Real-Time Shot-Cut Detection in a Compressed Domain,” Journal of Electronic Imaging, SPIE, vol. 16, no. 4, pp. (043011)1-6, 2007.
[7] X. Mo, Q. Yang, X. Zhang, J. Chen, Q. Wen, “Contrastive Representation for Dermoscopy Image Few-Shot Classification,” 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP 2020), pp. 134-137, 2020.
[8] J. Chen, J. Bao, S. Wang, Q. Yang, “Meta-Learning Approach Towards Microvessel Classification Based on PAC-Bayes,” 10th International Conference on Graphics and Image Processing (ICGIP 2018), 2018.
[9] J. Chen, Y. Liu, Y. Liu, S. Wang, S. Chen, “A Few-Shot Learning Framework for Air Vehicle Detection by Similarity Embedding,” 10th International Conference on Graphics and Image Processing (ICGIP 2018), 2018.
[10] S. Zhou, J. Chen, Q. Wen, “A Weight-based Optimization Algorithm of Histogram Equalization,” The 9th International Symposium on Advanced Optical Manufacturing and Testing Technology: Optoelectronic Materials and Devices for Sensing and Imaging (AOMATT), 2018.
[11] A. Sajjanhar, Z. Wu, J. Chen, Q. Wen, and R. Xiamixiding, “Experimental Evaluation of Facial Expression Recognition,” 2017 10th IEEE International Congress on Image and Signal Processing (CISP), pp. 1-5, 2017.
[12] A. A. Mohammed, R. Xiamixiding, A. Sajjanhar, J. Chen, and G. Nasierding, “Texture Features for Clustering Based Multi-Label Classification of Face Images,” 2017 10th IEEE International Congress on Image and Signal Processing (CISP), pp. 1-5, 2017.
[13] Q. Wen, J. Chen, and W. Liu, “Biologically Inspired Classification of Microvessel Histopathology via Sparse Coding,” 2013 6th IEEE International Conference on Advanced Computational Intelligence (ICACI), pp. 114-118, 2013.
[14] Q. Wen, J. Chen, and W. Liu, “A Predictive Coding Approach on Microvessel Identification via Single-Opponent Signal,” 2013 6th IEEE International Congress on Image and Signal Processing (CISP), pp. 1530-1534, 2013.
[15] Q. Wen, J. Chen, and W. Liu, “Quantitative Analysis on Mobility Behaviors of Fluorescent Marker Proteins Using Graph Model,” 2013 6th IEEE International Congress on Image and Signal Processing (CISP), pp. 670-674, 2013.
[16] D. Ming, Q. Wen, J. Chen, and W. Liu, “A Generalized Fusion Approach for Segmenting Dermoscopy Images Using Markov Random Field,” 2013 6th IEEE International Congress on Image and Signal Processing (CISP), pp. 532-537, 2013.
[17] Q. Wen, D. Ming, and J. Chen, “A Novel Fusion Approach for Segmenting Dermoscopy Image Based on Region Consistency,” 2013 IEEE International Conference on Computational Problem-Solving (ICCP), pp. 267-270, 2013.
[18] D. Ming, Q. Wen, J. Chen, and W. Liu, “A Superpixel Based Post-Processing Approach for Segmenting Dermoscopy Images,” 2013 6th IEEE International Conference on Advanced Computational Intelligence (ICACI), pp. 155-158, 2013.
[19] Q. Wen, W. Qu, J. Chen, and M. Mete, “A Novel Method for Counting Subcellular Structures Labeled by Green Fluorescent Protein,” IEEE International Conference on Computational Problem-Solving (ICCP), pp. 500-503, 2012.
[20] J. Chen, Q. Wen, C. Zhuo, and M. Mete, “Extraction of Color Entropy Sequence for Micro-vessel Detection in Virtual Slide,” IEEE International Congress on Image and Signal Processing (CISP), pp. 871-875, 2012.
[21] J. Chen, Q. Wen, W. Qu, and M. Mete, “Panda Facial Region Detection Based on Topology Modelling,” IEEE International Congress on Image and Signal Processing (CISP), pp. 911-915, 2012.
[22] J. Chen, Q. Wen, C. Zhuo, and M. Mete “Automatic Head Detection for Passenger Flow Analysis in Bus Surveillance Videos,” IEEE International Congress on Image and Signal Processing (CISP), pp. 143-147, 2012.
[23] J. Chen, Q. Wen, C. Zhuo, and M. Mete, “A Novel Approach Towards Head Detection of Giant Pandas in the Free-Range Environment,” IEEE International Congress on Image and Signal Processing (CISP), pp. 814-818, 2012.
[24] J. Chen, Q. Wen, Z. Pang, and M. Mete, “An Effective Approach Towards Color Image Segmentation for Micro-Vessel Detection,” IEEE International Conference on Computational Problem-Solving (ICCP), pp. 59-63, 2012.
[25] J. Chen, Q. Wen, C. Zhuo, and M. Mete, “Pose Recognition of Giant Pandas Based on Gradient Shapes,” IEEE International Conference on Computational Problem-Solving (ICCP), pp. 358-362, 2012.
[26] M. Mete, J. Chen, Q. Wen, and X. Liu, “Color Region Annotation for Microvessel Density Estimation,” IEEE International Conference on Wavelet Active Media Technology and Information Processing(ICWAMTIP), pp. 145-148, 2012.
[27] M. E. Celebi, Q. Wen, and J. Chen, “Color Quantization Using C-Means Clustering Algorithms,” IEEE International Conference on Image Processing (ICIP), pp. 1729-1732, 2011.
[28] J. Chen, “Detection of Video Copies based on Robust Descriptors,” IEEE International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA), pp.303-306, 2010.
[29] J. Chen, “Annotation of Fighting Scenes with Moving and Changing Backgrounds,” IEEE International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA), pp.271-274, 2010.
[30] J. Chen, S.S. Ipson and J. Jiang, “A Fuzzy Logic Method of Feature Representation for Shot Boundary Detection,” 2009 IEEE International Conference on Image Processing (ICIP), vol. 2, pp. 4337-4340, 2009.
[31] J. Chen and J. Jiang, “University of Bradford at TRECVID 2008: Content Based Copy Detection Task,” TREC Video Retrieval Evaluation On-line Proceedings, 2008.
[32] J. Chen, J. Ren and J. Jiang, “Compressed-Domain Shot Boundary Detection using Finite State Machine and Content-based Rules,” 2007 Asia-Pacific Workshop on Visual Information Processing (VIP), Taiwan. pp. 137-142, 2007.
[33] J. Ren, J. Jiang and J. Chen, “Determination of Shot Boundary in MPEG Videos for TRECVID 2007,” TREC Video Retrieval Evaluation On-line Proceedings, 2007.
[34]文泉，陈文宇，陈娟.面向“新工科”的目标跟踪实验设计.实验技术与管理. 2021.
[35]陈娟,刘锋林,黄麒之,文泉.基于成果导向教学的人工智能课程改革.软件导刊. 2020, 19(12): 19-22.
[36]文泉，张懿虎，陈娟.面向OBE和新工科的统计学习课程实践案例.计算机教育. (4):82-84, 2021.
[37]陈娟,杨倩,文泉,刘歆浏,刘议聪.面向“挑战性课程”的多目标跟踪实验设计.实验技术与管理. 37(1):155-158, 2020.
[38]陈娟,杨倩,何知蔓.面向“互联网+通识教育”的统计学习课程教学改革与实践.理解?沟通?共享——川渝通识教育探索. 23-29, 2019.
[39]陈娟,陈文宇,文泉,刘帛灵.面向新工科建设与创新人才培养的《统计学习理论及应用》教学改革与探索.“新工科与一流本科建设”研讨会暨中国高等教育学会工程教育专业委员会2019年年度会议. 303-310, 2019.
[40]文泉，陈文宇，陈娟，尹祥.以产学合作为契机建设面向新工科的《人工智能》课程的探索与思考. “新工科与一流本科建设”研讨会暨中国高等教育学会工程教育专业委员会2019年年度会议. 260-269, 2019.
[41]陈娟,文振宇,李志强,李天鹏.快速手势识别的实验设计.实验科学与技术. 9(6): 34-36, 2011.
[42]陈娟, ACM程序设计竞赛探讨.实验科学与技术. 8(6): 128-129, 2010.
[43]陈娟,视频镜头边界检测的实验设计.实验科学与技术. 8(2): 57-59, 2010.

研究成果获奖：
[1]《面向“新工科”的目标跟踪实验设计》获第四届中国计算机实践教育学术会议（CPEC2020），暨第十三届全国高等学校计算机实践教学论坛（“人工智能与计算机实践教育创新”方向）优秀论文二等奖。
[2]“基于智能电视电子节目单的大数据挖掘系统”，获2016年首届中国创新挑战赛（绵阳高新区赛区）优秀奖。
社会兼职及荣誉：
[1]担任International Journal of Biometrics and Bioinformatics (IJBB)编委。
[2]担任International Congress on Image and Signal Processing (CISP 2017, 2016, 2015, 2014, 2013, 2012, 2011)和International Conference on Graphics and Image Processing (ICGIP 2018, 2019, 2020, 2021)大会程序委员会委员。