姓名：吴永飞
职称：副教授，博士，硕士生导师
Email: wuyongfei@tyut.edu.cn
专业方向：数据科学与大数据技术，计算机技术与应用，计算数学，应用数学
研究领域：计算机视觉与模式识别，智能医学图像处理，机器学习，深度学习
承担项目
[1] 基于多特征融合和多尺度分解的变分自然图像分割方法研究，国家自然科学基金，主持
[2] 嵌入视觉显著性结构特征的变分图像分割方法研究，山西省青年科技研究基金项目，主持
[3] 基于变分水平集的红外小目标分割，山西省高等学校科技创新项目，主持
[4] 城市智能交通系统，山西省重点研发计划，参与
[5] 非凸非光滑高阶变分正则和非局部变分正则图像复原研究，国家自然科学基金，参与
[6] 基于变分PDE的显著特征提取及其在图像检索中的研究，国家自然科学基金，参与
学术成果
发表文章：
[24] Jiazi Ouyang, Xi Wu, Xuetao Ma, Yongfei Wu*, Chen Wang, Kidney whole slide image quality assessment based on fused convolutional neural networks, International Conference on Information Technology & Computer Application, ITCA2021, Guangzhou.
[23] Liang Zhang, Ming Li*, Yongfei Wu*, Fang Hao, Chen Wang, et al., Classification of renal biopsy direct immunofluorescence image using multiple attention convolutional neural network, Computer Methods and Programs in Biomedicine, 2021, 106532.
[22] Xueyu Liu, Ming Li, Yongfei Wu, et al., An efficient glomerular object locator for renal whole slide images using proposal-free network and dynamic scale evaluation method, Ai Communications, 2021, http://doi.org/10.3233/AIC-210073
[21] Xinyu Li, Ming Li, Yongfei Wu, et al. Accurate screw detection method based on faster R-CNN and rotation edge similarity for automatic screw disassembly, International Journal of Computer Integrated Manufacturing, 2021, http://dor.org/10.1080/0951192X.2021.1963476
[20] Xilin Liu, Yongfei Wu, Hao Zhang, Jiasong Wu, Liming Zhang, Quaternion discrete fractional Krawtchouk transform and its application in color image encryption and watermarking, Signal Processing, 2021, 108275.
[19] Yongfei Wu, Xilin Liu, Peiting Gao, Zehua Chen, A variational level set model with closed-form solution for bimodal image segmentation, Multimedia Tools and Applications, 2021, 80 (17) 1-21. https://doi.org/10.1007/s11042-021-10926
[18] Yongfei Wu, Liming Zhang, Tao Qian, Xilin Liu, Qiwei Xie, Content-adaptive image encryption with partial unwinding decomposition, Signal Processing, 2021, 181, 107911.
[17] Keshu Li, Ming Li, Yongfei Wu, et al., An Accurate Urine Erythrocytes Detection Model Coupled Faster RCNN with VggNet, Conference on Artificial Intelligence and Healthcare, CAIH2020, Taiyuan.
[16] Jiaojiao Feng, Ming Li, Yongfei Wu, et al., Urinary Red Blood Cells Extraction Based on Multiple Instance Learning and Watershed Segmentation, Conference on Artificial Intelligence and Healthcare, CAIH2020, Taiyuan.
[15] Xi Wu, Yongfei Wu, Xinyu Li, et al., Urine Red Blood Cells Generation Using StyleGAN2 Network, Conference on Artificial Intelligence and Healthcare, CAIH2020, Taiyuan.
[14] Xinyu Li, Ming Li, Yongfei Wu, et al., An accurate classification method based on multi-focus videos and deep learning for urinary red blood cell, Conference on Artificial Intelligence and Healthcare, CAIH2020, Taiyuan.
[13] Yilin Chen, Ming Li, Yongfei Wu, et al., MSA-MIL: A deep residual multiple instance learning model based on multi-scale annotation for classification and visualization of glomerular spikes, arXiv preprint arXiv:2007.00858.
[12] Yongfei Wu, Xilin Liu, Daoxiang Zhou, Yang Liu, Adaptive active contour model driven by image data field for image segmentation with flexible initialization, Multimedia Tools and Applications, 2019, DOI: 10.1007/s11042-019-08098-8
[11] Xilin Liu, Yongfei Wu, Zhuhong Shao, Jiasong Wu, The modified generic polar harmonic transforms for image representation, Pattern Analysis and Applications, 2019:1-11.
[10] Yang Liu, Chuanjiang He, Peiting Gao, Yongfei Wu, Zemin Ren, A binary level set variational model with L1 data term for image segmentation, Signal Processing, 2019, 155: 193–201.
[9] Xilin Liu, Yongfei Wu, Zhuhong Shao, Jiasong Wu, Huazhong Shu, Color image watermarking using a discrete trinion Fourier transform, Journal of Electronic Imaging, 2018, 27(4), 043046.
[8] Yang Liu, Chuanjiang He, Yongfei Wu, Zemin Ren, The L0-regularized discrete variational level set method for image segmentation, Image and Vision Computing, 2018, 75: 32–43.
[7] Yang Liu, Chuanjiang He, Yongfei Wu, Variational model with kernel metric-based data term for noisy image segmentation, Digital Signal Processing, 2018, 78: 42–55.
[6] Yongfei Wu*, Meng Li, Qifeng Zhang, Yang Liu, A Retinex modulated piecewise constant variational model for image segmentation and bias correction, Applied Mathematical Modelling, 2018, 54, 697–709.
[5] Yongfei Wu, Chuanjiang He, Yang Liu, Moting Su, A Backscattering-Suppression-Based Variational Level-Set Method for Segmentation of SAR Oil Slick Images, IEEE Journal of Selected Topics in Applied Earth Observatios and Remote Sensing, 2017, 10(12): 5485–5494.
[4] Yushu Zhang, Wenying Wen, Yongfei Wu, Rui Zhang, Junxin Chen, Xing He, Deciphering an RGB color image cryptosystem based on Choquet fuzzy integral, Neural Computing and Applications, 2017, 28(1): 165–169.
[3] Yongfei Wu, Chuanjiang He, Indirectly regularized variational level set model for image segmentation, Neurocomputing, 2016, 171: 194–208.
[2] Yushu Zhang, Yantao Li, Wenying Wen, Yongfei Wu, Junxin Chen, Deciphering an image cipher based on 3-cell chaotic map and biological operations, Nonlinear Dynamics, 2015, 82(4): 1831–1837.
[1] Yongfei Wu, Chuanjiang He, A convex variational level set model for image segmentation, Signal Processing. 2015, 106: 123–133.
授权专利：
[1] 刘西林，吴永飞，岳俊宏，周稻祥. 一种分数阶Tchebichef变换域的双图像主动认证方法，专利号：ZL201910621103.2
科技竞赛
本科生：
美国大学生数学建模竞赛获二等奖3项，三等奖3项
全国大学生数学建模竞赛获省级一等奖3项
研究生：
全国研究生数学建模竞赛获国家二等奖1项
奖励与荣誉
2021年荣获集团优秀毕业设计（论文）指导教师
2018年荣获集团优秀共产党员
2017年荣获集团优秀团学指导教师
重大项目、课题评审
国家自然科学基金项目函评专家
学术团体担任职务
ACM会员, CCF会员, CSIAM终身会员
