2011年毕业于复旦大学电子工程系获得理学博士学位，同年到云南大学信息学院任教，2012年获得“清华携手Google助力西部教育项目”人才引进励教金，2013年被遴选为云南大学中青年骨干教师。主要研究方向：基于生物机理的计算机视觉、图像处理与识别、云南壁画文化遗产数字化保护修复、人工神经网络、深度学习、机器学习、智能信息处理等。科研课题主要在基于生物机理的视觉信息计算模型方面，是当今计算机科学与认知科学交叉领域的热门研究课题。科研成果主要应用于遥感和雷达图像的地物目标检测、选择性视觉注意机制下的图像分割、压缩感知、图像修复等应用技术领域。在 Neurocomputing、Neural Processing Letters、Frontiers in Neurorobotics、Cognitive Neurodynamics、 IEEE Signal Processing Letters、IEEE Geoscience and Remote Sensing Letters、Heritage Science、《计算机辅助设计与图形学学报》、《模式识别与人工智能》、《电子与信息学报》、《计算机科学》、《国防科技大学学报》等国内外学术期刊以及 ICONIP、ISNN、ROBIO、IET IRC等国际会议上发表论文 40 余篇。获授权发明专利 4 项。

(1) 主持国家自然科学基金项目“基于视觉感知和认知机理的云南少数民族壁画数字修复关键技术研究”，2022/01-2025/12

(2) 主持国家自然科学基金项目“面向复杂场景自动目标检测和识别的变换域视觉注意模型研究”，2013/01-2016/12

(3) 承担国家自然科学基金项目“基于频域的选择性视觉注意模型及在遥感图像中的应用”，2011/01-2013/12

(4) 主持云南省应用基础研究计划面上项目“面向复杂场景的新型视觉注意计算模型研究”，2018/06-2021/05

(5) 主持云南大学中青年骨干教师培养计划项目，2013/09-2016/09

(6) 主持云南省教育厅科研基金项目 "基于变换域的选择性视觉注意模型研究"，2012/07-2014/06

(7) 主持云南大学科研基金项目 “选择性视觉注意频域模型及在图像处理中的应用研究”，2012/01-2013/12

(8) 参与云南省高等学校省级教学团队建设项目 “信号处理系列课程教学团队”, 2012/09-2015/08

(9) 参与云南大学教育教学改革立项项目“以信号处理系列课程为平台探究式教学为方式着力培养学生科研能力”，2016/01-2017/12

(10) 参与云南省应用基础研究计划面上项目“基于深度鉴别稀疏流形子空间学习网络的室内场景分类研究”，2016/06-2019/05

(11) 指导云南大学第十三届研究生科研创新项目“云南古壁画中缺陷自动标定关键技术研究”，2021/11-2023/03

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2018级研究生杨昊荣升华中科技大学人工智能与自动化学院博士生。

PS: 考研调剂事宜请咨询研究生院（办）

[1] Xiaochao Deng, Ying Yu (Corresponding author). Automatic calibration of crack and flaking diseases in ancient temple murals. Heritage Science, 2022, to appear. 

[2] Ying Yu, Jun Qian, Qinglong Wu. Visual Saliency via Multiscale Analysis in Frequency Domain and Its Applications to Ship Detection in Optical Satellite Images. Frontiers in Neurorobotics, 2022, 15: 767299. 

[3] Ying Yu, Jian Yang. Visual Saliency Using Binary Spectrum of Walsh–Hadamard Transform and Its Applications to Ship Detection in Multispectral Imagery. Neural Processing Letters, Springer, 2017, 45(3): 759-776.

[4] Ying Yu, Bin Wang, Liming Zhang. Saliency-Based Compressive Sampling for Image Signals. IEEE Signal Processing Letters, IEEE Press, 2010, 17 (11): 973-976.

[5] Ying Yu, Bin Wang, Liming Zhang. Hebbian-Based Neural Networks for Bottom-Up Visual Attention and Its Applications to Ship Detection in SAR Images. Neurocomputing, Elsevier, 2011, 74 (11): 2008-2017.

[6] Ying Yu, Bin Wang, Liming Zhang. Bottom-Up Attention: Pulsed PCA Transform and Pulsed Cosine Transform. Cognitive Neurodynamics, Springer, 2011, 5 (4): 321-332.

[7] Zhenghu Ding, Ying Yu, Bin Wang, Liming Zhang. An Approach for Visual Attention Based on Biquaternion and Its Application for Ship Detection in Multispectral Imagery. Neurocomputing, Elsevier, 2012, 76 (1): 9-17.

[8] Hao Shi, Liang Chen, Fu-kun Bi, He Chen, Ying Yu. Accurate Urban Area Detection in Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters, IEEE Press, 2015, 12 (9): 1948-1952.

[9] Dapeng Tao, Xipeng Yang, Weifeng Liu, Shuifa Sun, Yanan Guo, Ying Yu, Jianxin Pang. Cauchy Estimator Discriminant Learning for RGB-D Sensor-based Scene Classification. Multimedia Tools and Applications, Springer, 2017, 76 (3): 4471-4489.

[10] 余映, 王斌, 张立明. 一种面向数据学习的快速PCA算法. 《模式识别与人工智能》, 2009, 22(4): 567-573.

[11] 余映, 王斌, 张立明. 基于脉冲余弦变换的选择性视觉注意模型. 《模式识别与人工智能》, 2010, 23(5): 616-623.

[12] 丁正虎, 余映, 王斌, 张立明. 选择性视觉注意机制下的多光谱图像舰船检测. 《计算机辅助设计与图形学学报》, 2011, 23(3): 419-425.

[13] 余映, 杨鉴. 用于显著性检测的除法归一化方法. 《计算机辅助设计与图形学学报》, 2015, 27(9): 1759-1766.

[14] 吴青龙，敖成刚，余映（通讯作者）. 基于视觉中心及超像素空间加权的图像显著性检测. 《云南大学学报（自然科学版）》, 2018, 40(5): 848-854.

[15] 邵凯旋，余映（通讯作者），钱俊，等. 基于边缘信息结合空间权重的图像显著性检测算法研究. 《云南大学学报（自然科学版）》, 2020, 42(3): 429-436.

[16] 余映，吴青龙，邵凯旋，等. 超复数域小波变换的显著性检测. 《电子与信息学报》，2019, 41(9): 2231-2238.

[17] 吴青龙，余映（通讯作者），等. 基于频域多尺度分析的显著性检测. 《计算机辅助设计与图形学学报》, 2020, 32(1): 68-78.

[18] 李世镇，钱俊，余映（通讯作者），等. 基于凸包计算和颜色特征的显著性检测算法. 《云南大学学报（自然科学版）》, 2021, 43(2): 254-262.

[19] 杨昊，余映（通讯作者）. 利用通道注意力与分层残差网络的图像修复. 《计算机辅助设计与图形学学报》, 2021, 33(5): 671-681.

[20] 徐超越, 余映（通讯作者）, 何鹏浩, 李淼, 马玉辉. 基于U‐Net 的多尺度低照度图像增强网络. 《计算机工程》, 2022, 48(8): 215-223.

[21] 余映, 徐超越, 李淼, 何鹏浩, 杨昊. 金字塔渐进融合低照度图像增强网络. 《国防科技大学学报》, 2022.

[22] 余映, 何鹏浩, 徐超越. 基于残差注意力融合和门控信息蒸馏的图像修复. 《华南理工大学学报（自然科学版）》, 2022.

[23] 何鹏浩, 余映（通讯作者）, 徐超越. 基于动态金字塔和子空间注意力的图像超分辨率重建网络. 《计算机科学》, 2022.

[24] Ying Yu, Fukun Bi, et al. Saliency-Based Ship Detection in SAR Images. Proceedings of IET International Radar Conference (IET IRC 2015), IET Publication, pp. 1-5.

[25] Ying Yu, Jie Lin, et al. Bottom-Up Visual Saliency Using Binary Spectrum of Walsh-Hadamard Transform. Proceedings of the 21st International Conference on Neural Information Processing (ICONIP2014), Springer, Part III, Lecture Notes in Computer Science 8836, pp. 33–41.

[26] Ying Yu, Jie Lin, et al. Saliency Detection: A Divisive Normalization Approach. Proceedings of 2014 International Symposium on Neural Networks (ISNN2014), Springer Lecture Notes in Computer Science 8866, pp. 303-311.

[27] Ying Yu, Zhenghu Ding, Bin Wang, Liming Zhang. Visual Attention-Based Ship Detection in SAR Images. Proceedings of 2010 International Symposium on Neural Networks (ISNN2010), Springer Leture Notes in Electrical Engineering 67, pp.283–292.

[28] Ying Yu, Bin Wang, Liming Zhang. Hebbian-Based Neural Networks for Bottom-Up Visual Attention Systems. Proceedings of the 16th International Conference on Neural Information Processing (ICONIP2009), Springer, Part I, Lecture Notes in Computer Science 5863, pp.1–9.

[29] Ying Yu, Bin Wang, Liming Zhang. Pulse Discrete Cosine Transform for Saliency-Based Visual Attention. Proceedings of 2009 IEEE International Conference on Development and Learning (IEEE-ICDL 2009), IEEE Explore, pp. 1-6.

[30] Ying Yu, Jian Yang, Dan Xu. Towards Natural Image Denoising by Sparse Code Shrinkage: Improvements and Applications. Proceedings of 2007 International Conference on Intelligent Systems and Knowledge Engineering, France: Atlantis Press, pp.1423-1430.

[31] Ying Yu, Jian Yang. A New Method of Image Feature Extraction and Denoising Based on Independent Component Analysis. Proceedings of 2006 IEEE International Conference on Robotics and Biometics (IEEE-ROBIO 2006), IEEE Explore, pp.380-385.

[32] Xiaoting Yang, Fukun Bi, Ying Yu, Liang Chen. An Effective False-Alarm Removal Method Based on OC-SVM for SAR Ship Detection. Proceedings of IET International Radar Conference 2015, IET Publication, pp. 1-4.

[33] Long Ma, Bin Xu, Fukun Bi, He Chen, Ying Yu. Region of Interests Extraction Based on Visual Saliency for Remote Sensing Image. Proceedings of IET International Radar Conference 2015, IET Publication, pp. 1-4.

[34] Jinjing Shen, Long Ma, Liang Chen, He Chen, Ying Yu. A Novel Watershed Segmentation Method for SAR Image. Proceedings of IET International Radar Conference 2015, IET Publication, pp. 1-5.

[35] Hang Wei, Fukun Bi, Fuqiang Liu, Wenchao Liu, He Chen, Ying Yu. Water Body Extraction Based on The LBV Transformation Analysis for China GF-1 Multi-Spectral Images. Proceedings of IET International Radar Conference 2015, IET Publication, pp. 1-5.

[36] Fukun Bi, Jian Yang, Ying Yu, Dan Xu. Decision Templates Ensemble and Diversity Analysis for Segment-Based Speech Emotion Recognition. Proceedings of 2007 International Conference on Intelligent Systems and Knowledge Engineering, France: Atlantis Press, pp.1-5.

[37] Jun Qian, Ying Yu (Corresponding author) , Qinglong Wu. Bottom-Up Visual Saliency Based on Multiscale Analysis in Frequency Domain. to appear in Proceedings of 2020 International Symposium on Neural Network.

[38] Jun Qian, Ying Yu (Corresponding author)，Fukun Bi. Multi-Scale Saliency-based Ship Detection in SAR Images. Proceedings of IET International Radar Conference (IET IRC 2020), pp. 517-522.

[39] Hao Yang, Ying Yu (Corresponding author). Res2U-Net: Image Inpainting via Multi-Scale Backbone and Channel Attention. Proceedings of the 27th International Conference on Neural Information Processing (ICONIP2020), Springer, Lecture Notes in Computer Science 12532, pp. 498–508.

[40] Penghao He, Ying Yu (Corresponding author), Chaoyue Xu, Hao Yang. RAIDU-Net: Image Inpainting via Residual Attention Fusion and Gated Information Distillation. Proceedings of the 28th International Conference on Neural Information Processing (ICONIP2021).

[41] Yu-hui Ma, Ying Yu (Corresponding author). Multi-Scale Salient-Region Detection for Optical Remote Sensing Images. Proceedings of 2021 IEEE International Conference on Electronic Information Engineering and Computer Science (IEEE-EIECS 2021), pp. 1-6.

[42] Xingeng Zhu, Ying Yu (Corresponding author), Linxia Yang and Xiaochao Deng. Bring Ancient Murals Back to Life. to appear in Proceedings of the 29th International Conference on Neural Information Processing (ICONIP2022).