个人简介
方乐缘，湖南大学电气与信息工程学院教授，博士生导师，自动化系系主任，入选国家“优秀青年基金”、“湖湘英才计划”，岳麓********、IEEE Senior Member。担任图像处理与人工智能领域知名期刊IEEE Transactions on Image Processing、IEEE Transactions on Neural Networks and Learning System、IEEE Transactions on Geoscience and Remote Sensing、Neurocomputing编委（Associate Editor）。获得国家自然科学二等奖（排名第二）、湖南省自然科学一等奖（排名第二）、IEEE Transactions on Geoscience and Remote Sensing最佳审稿人等奖项。现主要从事深度学习、弱监督学习、遥感和医学图像处理与分析等方面的研究。研究成果在国际权威期刊和会议发表论文100余篇，其中SCI期刊发表论文80余篇（IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Medical Imaging, IEEE Transactions on Image Processing等本领域顶级IEEE会刊论文43篇），国际权威会议论文30篇，Google scholar引用超过5000余次，ESI高被引（1%）15篇，ESI热点论文（0.1%）4篇。
个人主页
科研在线：http://www.escience.cn/people/LeyuanFang/index.html
Google Site: https://sites.google.com/site/leyuanfang/home
Google scholar: https://scholar.google.com/citations?user=Gfa4nasAAAAJ&hl=zh-CN
主要研究方向及招生
深度学习、人工智能及其在医学与遥感图像处理、分析中的应用
在以上研究方向上，课题组与杜克大学、斯坦福大学、慕尼黑工业大学、德国宇航局、墨尔本大学、冰岛大学及中南大学湘雅医学院、湖南中医药大学、国家海洋局等国内外科研院所保持密切的科研合作关系
课题组常年招收博士后，博士，硕士及本科实习生：
课题组还有若干2021硕士、博士生指标，欢迎感兴趣同学与我联系。
招收博士后、2021级博士生，如符合以下条件且对待遇感兴趣的，请email ： leyuan_fang@hnu.edu.cn 邮件标题请标明博士后或者博士生申请

博士后基本要求：在图像处理、模式识别等领域权威期刊（如：IEEE Transactions）发表论文>=2篇
基本年薪20-30万/年+住房补贴2.16万/年+科研奖励
博士生要求：在图像处理、模式识别等领域发表SCI期刊1篇，Python、Matlab编程能力较强，有积极的科研态度
要求：对研究具有较浓厚的兴趣，且具有较好数学、英语和编程（Matlab，Python，C）能力。具有实际工程项目经验/竞赛获得前三名次者优先
主要教育经历
2010.9-2015.6
湖南大学
控制科学与工程专业
博士，导师：李树涛

2011.9-2012.9
杜克大学
生物医学工程专业
联合培养博士生，导师：Sina Farsiu


主要工作经历
2017.02-至今
2016.8-2017.9
湖南大学 电气与信息工程学院 教授
杜克大学 生物医学工程系 博士后研究人员

2017.02-2019.11
湖南大学 电气与信息工程学院 副教授

2015.12-至今
湖南大学 电气与信息工程学院 博士生导师

2013.6-2016.12
湖南大学 电气与信息工程学院， 助理教授（讲师）


主要科研项目
1.国家优秀青年基金项目，图像重建与分析，2020-2022，130万元，主持
2. 国家自然科学基金面上基金项目(**),基于OCT图像多病变分析的视网膜疾病自动诊断方法研究，2018-2021，66万元，主持。
3. 国家自然科学基金青年基金项目(**),面向光学相干层析成像的三维结构化压缩感知方法研究，26.38万元，2016.01-2018.12，主持。
4. 湖湘英才，2020-2022，50万元，主持
5. 国家博士后面上一等资助项目， 8万元，2016.06-2017.12，主持。
6. 国家博士后面上特别资助项目，15万元，2017.06-2018.12，主持。
7. 湖南省自然科学基金项目，5万元，2018.01-2019.12，主持。
8. 国家自然科学基金国际(地区)合作与交流项目,，高分辨率高光谱遥感图像信息获取与处理，245万元，2016.01-2020.12，参与。
代表性论文
大部分论文和源代码可在个人主页下载：http://www.escience.cn/people/LeyuanFang/index.html

1. Nanjun He, Leyuan Fang, Shutao Li, Javier Plaza, and Antonio Plaza, Skip-Connected Covariance Network for Remote Sensing Scene Classification, IEEE Transactions on Neural Networks and Learning Systems, In Press, 2020.
2. Jie Xie, Nanjun He, Leyuan Fang, and Pedram Ghamisi, Multiscale Densely-Connected Fusion Networks for Hyperspectral Images Classification, IEEE Transactions on Circuits and Systems for Video Technology, In Press, 2020.
3. Nanjun He, Leyuan Fang, and Antonio Plaza, Hybrid First and Second Order Attention Network for Building Segmentation in Remote Sensing Images, SCIENCE CHINA Information Sciences, In Press, 2020.
4. Jianjun Lei, Xiaowei Luo, Leyuan Fang, Yanfeng Gu, Region-Enhanced Convolutional Neural Network for Object Detection in Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, In Press, 2020.
5. Renwei Dian, Shutao Li, Leyuan Fang, Ting Lu, and José M. Bioucas-Dias, Nonlocal Sparse Tensor Factorization for Semiblind Hyperspectral and Multispectral Image Fusion, IEEE Transactions on Cybernetics, In Press, 2020.
6. Zhihong Huang, Shutao Li, and Leyuan Fang, Subpixel-Pixel-Superpixel Guided Fusion for Hyperspectral Anomaly Detection, IEEE Transactions on Geoscience and Remote Sensing, In Press, 2020.
7. Zhimin Shao, Zexin Lu, Maosong Ran, Leyuan Fang, Jiliu Zhou, and Yi Zhang, Residual Encoder-Decoder Conditional Generative Adversarial Network for Pansharpening, IEEE Geoscience and Remote Sensing Letters, In Press, 2020.
8. Yun Lin, Shutao Li, Leyuan Fang, and Pedram Ghamisi, Multispectral Change Detection With Bilinear Convolutional Neural Networks, IEEE Geoscience and Remote Sensing Letters, In Press, 2020.
9. Leyuan Fang, Wenke Zhao, Nanjun He, and Jian Zhu, Multiscale CNNs Ensemble Based Self-Learning for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, In Press, 2020.
10. Yan Cao, Leyuan Fang, Nanjun He, and Ting Lu, Self-attention Based Deep Feature Fusion for Remote Sensing Scene Classification, IEEE Geoscience and Remote Sensing Letters, In Press, 2020.
11. Laifeng Huang, Xinxin He, Leyuan Fang, Hossein Rabbani, and Xiangdong Chen, Automatic Classification of Retinal Optical Coherence Tomography Images With Layer Guided Convolutional Neural Network, IEEE Signal Processing Letters, 2019, 26(7): 1026-1030.
12. Yongqiang Huang, Zexin Lu, Zhimin Shao, Maosong Ran, Jiliu Zhou, Leyuan Fang, and Yi Zhang, Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network, Optics Express, 2019, 27(9): 12289-12307.
13. Jie Xie, Nanjun He, Leyuan Fang, and Antonio Plaza, Scale-free convolutional neural network for remote sensing scene classification, IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(9): 6916-6928.
14. Shutao Li, Weiwei Song, Leyuan Fang, Yushi Chen, Pedram Ghamisi, and Jón Atli Benediktsson, Deep learning for hyperspectral image classification: An overview, IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(9): 6690-6709.
15. Weiwei Song, Shutao Li, Leyuan Fang, Hyperspectral Images Classification with Deep Feature Fusion Network, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(6): 3173-3184. (Hot Paper and Highly Cited Paper in Web of Science)
16. Leyuan Fang, Shutao Li, Wuhui Duan, Jinchang Ren, and Jón Benediktsson, Classification of hyperspectral images by exploiting spectral-spatial information of superpixel via multiple kernels, IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(12): 6663-6674. (Highly Cited Paper in Web of Science)
17. Leyuan Fang, Shutao Li, Xudong Kang, and Jón Benediktsson, Spectral-spatial classification of hyperspectral images with a superpixel based discriminative sparse model, IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(8): 4186-4201. (Highly Cited Paper in Web of Science)
18. Leyuan Fang, Shutao Li, Xudong Kang, and Jón Benediktsson, Spectral-spatial hyperspectral image classification via multiscale adaptive sparse representation, IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(12): 7738-7749. (Highly Cited Paper in Web of Science)
19. Leyuan Fang, Nanjun He, Shutao Li, J. Benediktsson, Extinction Profiles Fusion for Hyperspectral Images Classification, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(3): 1803-1815. (Highly Cited Paper in Web of Science)
20. Leyuan Fang, Nanjun He, Shutao Li, Antonio Plaza, Javiar Plaza, A New Spatial–Spectral Feature Extraction Method for Hyperspectral Images Using Local Covariance Matrix Representation, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(6): 3534-3546. (Highly Cited Paper in Web of Science)
21. Leyuan Fang, Guangyun Liu, Shutao Li, Hyperspectral Image Classification with Squeeze Multi-Bias Network, IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(3): 1291-1301. (Highly Cited Paper and Hot paper in Web of Science)
22. Yue Wu, Shutao Li, and Leyuan Fang, Weighted Tensor Rank-1 Decomposition for Nonlocal Image Denoising, IEEE Transactions on Image Processing, 2019, 28(6), 2719-2730.
23. Shutao Li, Renwei Dian, Leyuan Fang, Bioucas Dias Jose M, Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization, IEEE Transactions on Image Processing, 2019, 27(8): 4118~4130.
24. Nanjun He, Leyuan Fang, Shutao Li, Antonio Plaza, Javiar Plaza, Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(12): 6899-6910.
25. Jessica Loo, Leyuan Fang, David Cunefare, Geffine J Jaffe, Sina Farsiu, Deep longitudinal transfer learning-based automatic segmentation of photoreceptor ellipsoid zone defects on optical coherence tomography images of macular telangiectasia type 2, Biomedical Optics Express, 2018, 9(6): 2681-2698.
26. Nanjun He, Leyuan Fang, Shutao Li, Antonio Plaza, Javiar Plaza, Feature Extraction with Multiscale Covariance Maps for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(2): 755-769. (Highly Cited Paper and Hot paper in Web of Science)
27. Wei Fu, Shutao Li, Leyuan Fang, Jon Benediktsson, Contextual Online Dictionary Learning for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(3): 1336-1347.
28. Ting Lu, Shutao Li, Leyuan Fang, Lorenzo Bruzzone, and Jon Atli Benediktsson, Set-to-set distance-based spectral-spatial classification of hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12): 7122-7134.
29. Shutao Li, Ting Lu, Leyuan Fang, Xiuping Jia, and Jon Atli Benediktsson, Probabilistic Fusion of Pixel-Level and Superpixel-Level Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12): 7416-7430.
30. Xudong Kang, Shutao Li, Leyuan Fang, and Jón Benediktsson, Intrinsic image decomposition for feature extraction of hyperspectral images，IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 2241-2253.
31. Wei Fu, Shutao Li, Leyuan Fang, Xudong Kang, and Jón Benediktsson, Adaptive Spectral-Spatial Compression of Hyperspectral Image With Sparse Representation, IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(2): 671-682.
32. Xudong Kang, Shutao Li, Leyuan Fang, Meixiu Li, and Jón Benediktsson, Extended random walker-based classification of hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(1): 144-153.
33. Shutao Li, Haitao Yin, and Leyuan Fang, Remote sensing image fusion via sparse representations over learned dictionaries, IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(9): 4779-4789.
34. Ting Lu, Shutao Li, Leyuan Fang, Yi Ma, and Jón Atli Benediktsson, Spectral-spatial adaptive sparse representation for hyperspectral image denoising, IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(1): 373-385.
35. Ting Lu，Shutao Li，Leyuan Fang，Xiuping Jia，Jón Atli Benediktsson，From Subpixel to Superpixel: A Novel Fusion Framework for Hyperspectral Image Classification，IEEE Transactions on Geoscience and Remote Sensing，2017, 55(8): 4398-4411.
36. Leyuan Fang, Cheng Wang, Shutao Li, Jón Benediktsson, Hyperspectral image classification via multiple-feature based adaptive sparse representation, IEEE Transactions on Instrumentation and Measurement, 2017, 66(7): 1646-1657, 2017. (Highly Cited Paper in Web of Science)
37. Leyuan Fang, Shutao Li, Davia Cunefare, and Sina Farsiu, Segmentation based sparse reconstruction of optical coherence tomography images, IEEE Transactions on Medical Imaging, 2017, 36(2): 407-421. (Highly Cited Paper in Web of Science)
38. Leyuan Fang, Chong Wang, Shutao Li, Hossein Rabbani, Xiangdong Chen, and Zhimin Liu, Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification, IEEE Transactions on Medical Imaging, 2019, In Press.
39. Renwei Dian, Shutao Li, and Leyuan Fang, Learning a Low Tensor-Train Rank Representation for Hyperspectral Image Super-Resolution, IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(9): 2672-2683.
40. Leyuan Fang, Shutao Li, Xudong Kang, Joseph Izatt, and Sina Farsiu, 3-D adaptive sparsity based image compression with applications to optical coherence tomography, IEEE Transactions on Medical Imaging, 2015, 34(6): 1306-1320.
41. Leyuan Fang, Shutao Li, Qing Nie, Ryan Mcnabb, Anthony Kuo, Cynthia Toth, Joseph Izatt, and Sina Farsiu, Fast acquisition and reconstruction of optical coherence tomography images via sparse representation, IEEE Transactions on Medical Imaging, 2013, 32(11): 2034-2049.
42. Shutao Li, Leyuan Fang, and Yin Haitao, An efficient dictionary learning algorithm and its application to 3-D medical image denoising, IEEE Transactions on Biomedical Engineering, 2012, 59(2):417-427.
43. Shutao Li, Haitao Yin, and Leyuan Fang, Group-sparse representation with dictionary learning for medical image denoising and fusion, IEEE Transactions on Biomedical Engineering, 2012, 59(12): 3450-3459.
44. Shutao Li and Leyuan Fang, Signal denoising with random refined orthogonal matching pursuit, IEEE Transactions on Instrumentation and Measurement, 2012, 61(1):26-34.
45. Haicang Liu, Shutao Li, and Leyuan Fang, Robust Object Tracking based on Principal Component Analysis and Local Sparse Representation, IEEE Transactions on Instrumentation and Measurement, 64(11): 2863-2875, 2015.
46. Renwei Dian, Shutao Li, Leyuan Fang, Deep Hyperspectral Image Sharpening, IEEE Transactions on Neural Networks and Learning System, 2018, 29(11): 5345-5355.
47. Leyuan Fang and Shutao Li, Face recognition by exploiting local gabor features via multi-task adaptive sparse representation, IEEE Transactions on Instrumentation and Measurement, 2015, 64(10): 2605-2615.
48. Ting Xie, Shutao Li, Leyuan Fang, Licheng Liu, Tensor Completion via Nonlocal Low-Rank Regularization, IEEE Transactions on Cybernetics, 2018, In Press
49. Leyuan Fang, David Cunefare, Chong Wang, Robyn H. Guymer, Shutao Li, and Sina Farsiu, Automatic segmentation of nine retinal layer boundaries in optical coherence tomography images using deep learning and graph search, Biomedical Optics Express, 2017, 8(5): 2732-2744. (Highly Cited Paper and Hot paper in Web of Science)
50. Leyuan Fang, Shutao Li, Qing Nie, Cynthia Toth, Joseph Izatt, and Sina Farsiu, Sparsity based denoising of spectral domain optical coherence tomography images, Biomedical Optics Express, 2012, 3(5):927-942. (selected as the ‘Feature of the week’ in OCTNews http://www.octnews.org)