冯松鹤

博士、教授、博士生导师

基本信息

办公电话:N/A 电子邮件: shfeng@bjtu.edu.cn
通讯地址:北京交通大学计算机学院9教北524 邮编:100044

个人简介

       北京交通大学计算机与信息技术学院教授,博士生导师,入选首批北京交通大学青年英才培育计划,担任北京市信息服务工程市重点实验室学术委员会委员主要研究领域为弱监督机器学习算法及其在图像语义理解中的应用。累计主持国家自然科学基金面上及青年项目3项,北京市自然科学基金面上项目2项,教育部博士点基金1项,中国博士后科学基金特别资助项目及面上项目各1项。在包括 IEEE Trans. on Pattern Analysis and Machine Intelligence, IEEE Trans. on Image Processing, IEEE Trans. on Knowledge and Data Engineering,  ACM Trans. on Knowledge Discovery from Data, IEEE Trans. on Multimedia, IEEE Trans. on Cybernetics, ACM Trans. on Intelligent Systems and Technology 等知名学术期刊以及 ACM SIGKDD, AAAI, IJCAI, ACM Multimedia, ICCV, ECCV, ECML-PKDD 等知名国际会议上累计发表各类研究论文近百篇。受国家留学基金委资助,分别于2014年及2017年在美国密歇根州立大学和德国德累斯顿工业大学任国家公派访问学者。

教育背景

  • 2003.09 - 2009.01  北京交通大学,计算机应用技术,直博,博士 (导师:须德 教授);
  • 1999.09 - 2003.07  北京交通大学,计算机科学与技术,学士;

工作经历

  • 2017.12 - 至今          北京交通大学,计算机与信息技术学院,教授;
  • 2017.09 - 2017.12   德累斯顿工业大学(德国),访问学者;
  • 2013.10 - 2014.10   密歇根州立大学(美国),访问学者 (合作导师:Rong Jin)
  • 2012.12 - 2017.11  北京交通大学,计算机与信息技术学院,副教授;
  • 2011.01 - 2012.11  北京交通大学,计算机与信息技术学院,讲师; 
  • 2009.04 - 2010.12  北京交通大学,计算机与信息技术学院,师资博士后

科研项目

       主持多项  国家自然科学基金项目 / 北京市自然科学基金项目 / 教育部博士点基金项目 / 博士后科学基金特别资助项目 / 基本科研业务费重点项目。 部分代表性主持科研项目列表如下:

  • 国家自然科学基金面上项目:弱监督学习框架下大规模图像语义理解关键技术研究,2019-2022, 主持在研
  • 北京自然科学基金面上项目:弱监督多标记学习算法研究及应用,2020-2022, 主持在研
  • 基本科研业务费重点资助项目:多视图学习算法关键技术研究,2022-2025,主持(在研
  • 国家自然科学基金面上项目:2015-2018, 主持(已结题)
  • 北京自然科学基金面上项目:2016-2018, 主持(已结题)
  • 家自然科学基金青年项目:2012-2014, 主持(已结题)
  • 教育部博士点基金新教师类项目:2012-2014, 主持(已结题)
  • 中国博士后科学基金特别资助项目:2010-2011, 主持(已结题)
  • 国家自然科学基金面上项目:2010-2012, 合作单位主持(已结题)

研究生培养

近五年来,指导研究生累计获得 校级优秀博士论文 1人/次校级优秀硕士论文 3人/次院级优秀硕士论文 4人/次

(A) 本人年招收博士研究生(直博/硕博连读:每年1名;申请考核:每年1名)!欢迎数学 / 信息与计算科学 / 计算机科学与技术专业同学邮件咨询!  

欢迎詹天佑学院的同学们联系!

(B) 本人常年招收硕士研究生(学术型:每年2-4名;专业型:每年2-3名)!欢迎 数学 / 信息与计算科学 / 计算机科学与技术相关专业的同学报考!      

欢迎2023级推免生,参加我院暑期夏令营的同学们提前联系

要求:1. 热爱科研,善于沟通与团队合作;

          2. 较为扎实的数学基础,英文读写能力,以及良好的编程能力;

          3. 有读博意愿的同学尽量选择报考学术型硕士研究生;

研究方向

  • 理论层面:聚焦于弱监督机器学习算法研究,包括多标记学习(Multi-Label Learning)、偏标记学习(Partial-Label Learning)、多视图聚类(Multi-View Clustering)、多视图多标记分类(Multi-View Multi-Label Learning)等;
  • 应用层面:聚焦于深度学习框架下的图像语义理解算法研究,包括但不限于:弱监督多标记图像分类(Multi-Label Image Classification)、小样本类增量学习(Few-Shot Class Incremental Learning)等;

招生专业

  • 计算机科学与技术硕士
  • 计算机技术硕士
  • 软件工程硕士
  • 人工智能硕士
  • 网络与信息安全硕士
  • 大数据技术与工程硕士
  • 计算机科学与技术博士
  • 计算机技术博士

在读研究生

博士研究生:  

  • 吴亚楠 (2019-)      
  • 谷志斌 (2020-) 
  • 王   靖 (2022-)

硕士研究生:    

  • 邓响 (2020-)  胡睿婷 (2020-)  刘威 (2020-)
  • 张阳 (2021-)  王佳艺 (2021-)  孙伟华 (2021-)  张展 (2021-)  翁昊晚 (2021-)  郭彤 (2021-)  
  • 季津天(2022-)  吴婷婷(2022-)   梁婧(2022-)  杨洪涛(2022-)  张仕瞳(2022-)

毕业研究生

博士:

  • 2022:吕庚育 (校级优秀博士论文 | 知行奖学金 | 宝钢奖学金 | 华为奖学金 | 国家奖学金) - 北京工业大学,副教授(校聘教授)
  • 2021:孙利娟 - 北京邮电大学,讲师 

硕士:

  • 2022:   陆迅 (校级优秀硕士论文);刘馨媛 (院级优秀硕士论文 | 国家奖学金);王绍凯 (院级优秀硕士论文);周彤;赵建国;任博伟
  • 2021:李子薇 (级优秀硕士论文 | 国家奖学金) 孙悦 (国家奖学金)
  • 2020:李振东 (校级优秀硕士论文)叶苹;刘燕;季玲玲;李艳青
  • 2019:权洪林 (级优秀硕士论文);黄文英;黄维雪
  • 2018:王晓莹 (校级优秀硕士论文)
  • 2017:李敬伟孙健                           
  • 2016:罗骁原邢妍妍翟昱昊           
  • 2014:谢延涛

论文/期刊

( ^表示作者均为本人指导的研究生,*表示本人为通讯作者)

News:

  • Yanan Wu^Songhe Feng*. Transformer Driven Matching Selection Mechanism for Multi-Label Image Classification. IEEE Trans. on Image Processing, 2022. (CCF A类, Accepted with Minor Revision)
  • Gengyu Lyu^Songhe Feng*. Redundant Label Learning via Subspace Representation and Global Disambiguation. ACM Trans. on Intelligent Systems and Technology, 2022. (Accepted) 
  • Tengfei Liang, Yi Jin, Wu Liu, Songhe Feng, Tao Wang, Yidong Li. Keypoint-Guided Modality-Invariant Discriminative Learning for Visible-Infrared Person Re-Identification. ACM Multimedia, 2022. (CCF A类, Accepted) 
  • Zhibin Gu^, Ruiting Hu^, Songhe Feng*. ONION: Joint Unsupervised Feature Selection and Robust Subspace Extraction for Graph-based Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data, 2022. (Major Revision)  
  • Gengyu Lyu^, Shaokai Wang^,Songhe Feng*. Prior Knowledge Constrained Adaptive Graph Framework for Partial Label Learning. ACM Trans. on Intelligent Systems and Technology, 2022. (Major Revision)
  • Yanan Wu^, Songhe Feng*. Semantic-Aware Graph Matching Mechanism for Multi-Label Image Recognition. 2022. (Submitted) 
  • Xiang Deng^, Songhe Feng*. Addressing Multi-Label Learning with Missing Labels: from Sample Selection to Label Selection. 2022. (Submitted) 
  • Zhibin Gu^, Songhe Feng*. ONESELF: One-Step Graph-based Multi-View Clustering via Early Fusion. 2022. (Submitted)
  • Gengyu Lyu^, Xiang Deng^Songhe Feng*. L-VSM: Label Driven View-Specific Fusion for Multi-View Multi-Label Learning. 2022. (Submitted)
  • Wei Liu^, Gengyu Lyu^Songhe Feng*Graph-based Multi-View Partial Multi-Label Learning. 2022. (Submitted)      

2022:

  • Gengyu Lyu^, Yanan Wu^, Songhe Feng*. Deep Graph Matching for Partial Label Learning. IJCAI, 2022. (CCF A类)
  • Gengyu Lyu^, Xiang Deng^, Yanan Wu^Songhe Feng*. Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning. AAAI, 2022. (CCF A类)
  • Xun Lu^, Songhe Feng*. Distance-Preserving Embedding Bipartite Graph Multi-View Learning with Application to Multi-Label Classification. ACM Trans. on Knowledge Discovery from Data. 2022. (CCF B类, Early Access)  
  • Xun Lu^Songhe Feng*.  Structure Diversity-Induced Anchor Graph Fusion for Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data. 2022. (CCF B类, Early Access) 
  • Zhibin Gu^, Songhe Feng*. Individuality Meets Commonality: A Unified Graph Learning Framework for Multi-View Clustering. ACM Trans. on Knowledge Discovery from Data. 2022. (CCF B类, Early Access)
  • Xiang Deng^Songhe Feng*. Beyond Word Embeddings: Heterogeneous Prior Knowledge Driven Multi-Label Image Classification. IEEE Trans. on Multimedia, 2022. (CCF B类, Early Access)
  • Lijuan Sun^Songhe Feng*. Global-Local Label Correlation for Partial Multi-Label Learning. IEEE Trans. on Multimedia, 24(2), pp. 581-593, 2022(CCF B类)
  • Gengyu Lyu^, Songhe Feng*. A Self-paced Regularization Framework for Partial-Label Learning. IEEE Trans. on Cybernetics, 52(2), pp. 899-911, 2022(CCF B类) 
  • Gengyu Lyu^, Songhe Feng*Prior Knowledge Regularized Self-Representation Model for Partial Multi-Label Learning. IEEE Trans. on Cybernetics. (CCF B类, Early Access)
  • Zhibin Gu^, Hongzhe Liu*, Songhe Feng*. Diversity Induced Consensus and Structured Graph Learning for Multi-View Clustering. Applied Intelligence, 2022. (Accepted)   
  • Wei Liu^Jiazheng Yuan*Gengyu Lyu^Songhe Feng*.  Label Driven Latent Subspace Learning for Multi-View Multi-Label Classification. Applied Intelligence, 2022. (Early Access)   
  • Shaokai Wang^, Mingxuan Xia^, Zilong Wang^, Gengyu Lyu^, Songhe Feng*. Partial Label Learning with Noisy Side Information. Applied Intelligence2022. (Early Access
  • Xinyuan Liu^, Lijuan Sun^, Songhe Feng*. Incomplete Multi-View Partial Multi-Label Learning. Applied Intelligence, 52(3), pp. 3289-3302, 2022.
  • Jianguo Zhao^, Gengyu Lyu^, Songhe Feng*. Linear Neighborhood Reconstruction Constrained Latent Subspace Discovery for Incomplete Multi-View Clustering. Applied Intelligence, 52(1), pp. 982-993, 2022.
  • Liqian Liang, Congyan Lang, Zun Li, Jian Zhao, Tao Wang, Songhe Feng. Seeing Crucial Parts: Vehicle Model Verification via A Discriminative Representation Model. ACM Trans. on Multimedia Computing, Communication, and Applications, 18(1), pp. 1-22, 2022. (CCF B类) 
  • Zun Li, Congyan Lang, Liqian Liang, Jian Zhao, Songhe Feng, Qibin Hou, Jiashi Feng. Dense Attentive Feature Enhancement for Salient Object Detection. IEEE Trans. on Circuits and Systems for Video Technology. (CCF B类, Early Access 
  • Yutong Gao, Liqian Liang, Congyan Lang, Songhe Feng, Yidong Li, Yunchao Wei. Clicking Matters: Towards Interactive Human Parsing. IEEE Trans. on Multimedia. (CCF B类, Early Access)
  • Lili Wei, Congyan Lang, Liqian Liang, Songhe Feng, Tao Wang, Shidi Chen. Weakly-Supervised Video Object Segmentation via Dual-Attention Cross-Branch Fusion. ACM Trans. on Intelligent Systems and Technology, 13(3), pp.1-20, 2022 
  • Xiuting You, He Liu, Tao Wang, Songhe Feng, Congyan Lang. Object Detection by Crossing Relational Reasoning based on Graph Neural Network. Machine Vision and Applications, 2022
  • Shi Qiu, Yi Jin, Songhe Feng, Tao Zhou, Yidong Li. Dwarfism Computer-Aided Diagnosis Algorithm based on Multimodal Pyradiomics. Information Fusion, pp. 137-145, 2022. 
  • Ruijie Zhao, Congyan Lang, Zun Li, Liqian Liang, Lili Wei, Songhe Feng, Tao Wang. Pedestrain Attribute Recognition based on Attribute Correlation. Multimedia System, pp. 1069-1081, 2022. 

2021:

  • Yanan Wu^, He LiuSonghe Feng*. GM-MLIC: Graph Matching based Multi-Label Image Classification. IJCAI, pp. 1179-1185, 2021. (CCF A类)   
  • Gengyu Lyu^, Songhe Feng*. GM-PLL: Graph Matching based Partial Label Learning.  IEEE Trans. on Knowledge and Data Engineering, 33(2), pp. 521-535, 2021(CCF A类)
  • Lijuan Sun^, Songhe Feng*. Partial Multi-Label Learning with Noisy Side Information. Knowledge and Information Systems, 63(2), pp. 541-564, 2021. (CCF B类)
  • Gengyu Lyu^, Songhe Feng*. Noisy Label Tolerance: A New Perspective of Partial Multi-Label Learning. Information Sciences, 543(1), pp. 454-466, 2021. (CCF B类)
  • Lijuan Sun^, Gengyu Lyu^, Songhe Feng*. Beyond Missing: Weakly-Supervised Multi-Label Learning with Incomplete and Noisy Labels, Applied Intelligence, 51(3), pp. 1552-1564, 2021. 
  • Yanan Wu^, Songhe Feng*. L4Net: An Anchor-Free Generic Object Detector with Attention Mechanism for Autonomous Driving. IET Computer Vision, 15(1), pp. 36-46, 2021. 
  • Tong Zhou^, Songhe Feng*. Multiple Semantic Embedding with Graph Convolutional Networks for Multi-Label Image Classification. PRCV, 2021. 
  • Liqian Liang, Congyan Lang, Yidong Li, Songhe Feng, Jian Zhao. Fine-Grained Facial Expression Recognition in the Wild. IEEE Trans. on Information Forensics and Security, 16(1), pp. 482-494, 2021. (CCF A类) 
  • Min Wang, Congyan Lang, Liqian Liang, Songhe Feng, Tao Wang, Yutong Gao. Fine-Grained Semantic Image Synthesis with Object Attention Generative Adversarial Network. ACM Trans. on Intelligent Systems and Technology, 12(5), pp. 1-18, 2021 
  • Min Wang, Congyan Lang, Songhe Feng, Tao Wang, Yi Jin, Yidong Li. Text to Photo-Realistic Image Synthesis via Chained Deep Recurrent Generative Adversarial Network. Journal of Visual Communication ans Image Representation, 74(1), 2021. 
  • Min Wang, Congyan Lang, Liqian Liang, Gengyu Lyu, Songhe Feng, Tao Wang. Class-balanced Text to Image Synthesis with Attentive Generative Adversarial Network. IEEE Multimedia, 28(3), pp. 21-31, 2021.

2020: 

  • Gengyu Lyu^, Songhe Feng. Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. ACM SIGKDD, pp. 105-113, 2020. (Research Track, CCF A)
  • Ziwei Li^, Gengyu Lyu^, Songhe Feng*. Partial Multi-Label Learning via Multi-Subspace Representation. IJCAI, pp. 2612-2618, 2020. (CCF A) 
  • Gengyu Lyu^, Songhe Feng*. HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization. ACM Trans. on Intelligent Systems and Technology, 11(3), 34: 1-34:19, 2020. 
  • Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Self-Paced Curriculum Learning, ECML-PKDD, pp. 489-505, 2020. (CCF B类)     
  • Yue Sun^, Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Subspace Representation and Global Disambiguation, ECML-PKDD, pp. 439-454, 2020. (CCF B类) 
  • Lijuan Sun^, Ping Ye^, Gengyu Lyu^, Songhe Feng*. Weakly-Supervised Multi-Label Learning with Noisy Features and Incomplete Labels. Neurocomputing, 413(6), pp. 61-71, 2020.
  • Gengyu Lyu^, Songhe Feng*. Partial Label Learning via Low-Rank Representation and Label Propagation. Soft Computing, pp. 5165-5176, 2020
  • Honglin Quan^, Songhe Feng*. Improving Person Re-identification via Attribute-identity Representation and Visual Attention Mechanism. Multimedia Tools and Applications, 79(11-12), pp. 7259-7278, 2020. 
  • Min Wang, Congyan Lang, Liqian Liang, Yutong Gao, Songhe Feng, Tao Wang. End-to-End Text-to-Image Synthesis with Spatial Constraints. ACM Trans. on Intelligent Systems and Technology, 11(4): 47:1-47:19, 2020.
  • Min Wang, Congyan Lang, Liqian Liang, Gengyu Lyu, Songhe Feng, Tao Wang. Attentive Generative Adversarial Network to Bridge Multi-Domain Gap for Image Synthesis. ICME, pp, 1-6, 2020. (CCF B类)
  • Zhongyi Li, Yi Ji, Yidong Li, Congyan Lang, Songhe Feng, Tao Wang.  Learning Part-Alignment Feature for Person Re-Identification with Spatial Temporal based Re-ranking Method. World Wide Web, 23(3), pp. 1907-1923, 2020. (CCF B)  
  • Zhenxing Zheng, Zhendong Li, Gaoyun An, Songhe Feng. Subgraph and Object Context-Masked Network for Scene Graph Generation. IET Computer Vision, 14(7), pp. 546-553, 2020. 
  • Yingxia Jia, Congyan Lang, Songhe Feng. A Semantic Segmentation Method of Traffic Scene Based on Categries-Aware Domain Adaption. Journal of Computer Research and Development, 2020. (In Chinese)  
  • Zheming Xu, Lili Wei, Congyan Lang, Songhe Feng, Tao Wang, Adrian G Bors. HSS-GCN: A Hierarchical Spatial Structure Graph Convolutional Network for Vehicle Re-Identification. ICPR, 2020.  

2019:

  • Lijuan Sun^, Songhe Feng*. Partial Multi-Label Learning by Low-Rank and Sparse Decomposition. AAAI, 2019. (CCF A)
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng, Xiaohui Hou. Deformable Surface Tracking by Graph Matching. ICCV, 2019. (CCF A)      
  • Xiaoying Wang^, Songhe Feng*. Semi-Supervised Dual Low-Rank Feature Mapping for Multi-Label Image Annotation.  Multimedia Tools and Applications, 78(10), pp. 13149-13168, 2019. 
  • Lijuan Sun^, Songhe Feng*. Robust Semi-Supervised Multi-Label Learning by Triple Low-Rank Regularization. PAKDD, 2019. 
  • Zun Li, Congyan Lang, Jiashi Feng, Yidong Li, Tao Wang, Songhe Feng. Co-Saliency Detection with Graph MatchingACM Trans. on Intelligent System and Technology, 10(3), 22:1-22:22, 2019. 
  • Yanan Dong, Congyan Lang, Songhe Feng*. General Structured Sparse Learning for Human Facial Age Estimation. Multimedia Systems, 25(1), pp. 49-57, 2019. 
  • Mengxia Yin, Congyan Lang, Zun Li, Songhe Feng, Tao Wang. Recurrent Convolutional Network for Video-based Smoke Detection. Multimedia Tools and Applications, 78(1), pp. 237-256, 2019. 
  • Bingqian Geng, Congyan Lang, Junliang Xing, Songhe Feng. MFAD: A Multi-modality Face Anti-spoofing Dataset. PRICAI, 2019. 
  • Ping Ye^, Songhe Feng*. Robust Multi-Label Learning with Corrputed Features and Incomplete Labels. CAC, 2019.       

2018:

  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Graph Matching with Adaptive and Branching Path Following.  IEEE Trans. on Pattern Analysis and Machine Intelligence, 40(12), pp. 2853-2867, 2018. (CCF A) 
  • Songhe Feng, Congyan Lang. Graph Regularized Low-rank Feature Mapping for Multi-label Learning with Application to Image Annotation. Multidimensional Systems and Signal Processing, 29, pp. 1351-1372, 2018. 
  • Wenying Huang^, Songhe Feng*. Partial Label Learning via Low-rank Representation and Label Propagation. ICIMCS, 2018.  
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Constrained Confidence Matching for Planar Object Tracking. ICRA, 2018. (CCF B)   
  • Zun Li, Congyan Lang, Songhe Feng, Tao Wang. Saliency Ranker: A New Salient Object Detection Method.  Journal of Visual Communication and Image Representation, 50(1), pp. 16-26, 2018.  
  • Jun Zhou, Tao Wang, Congyan Lang, Songhe Feng. A Novel Hypergraph Matching Algorithm based on Tensor Refining. Journal of Visual Communication and Image Representation, 57, pp. 69-75, 2018. 
  • Shaoyan Xu, Tao Wang, Congyan Lang, Songhe Feng, Yi Jin. Graph-based Visual Odometry for VSLAM. Industrial Robot, 2018.

2017

  • Songhe Feng, Congyan Lang, Jiashi Feng, Tao Wang, Jiebo Luo. Human Facial Age Estimation by Cost-Sensitive Label Ranking and Trace Norm Regularization. IEEE Trans. on Multimedia, 19(1), pp. 136-148, 2017. (CCF B)
  • Zhu Teng, Junliang Xing, Qiang Wang, Congyan Lang, Songhe Feng, Yi Jin. Robust Object Tracking Based on Temporal and Spatial Deep Networks. ICCV, 2017. (CCF A)   

2016

  • Congyan Lang, Jiashi Feng, Songhe Feng, Jingdong Wang, Shuicheng Yan. Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.  IEEE Trans. On Neural Networks and Learning Systems, 27(6), pp. 1190-1200, 2016. (CCF B)  
  • Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng. Symmetry-Aware Graph Matching. Pattern Recognition, 60, pp. 657-668, 2016. (CCF B 
  • Jingwei Li^, Songhe Feng*. Graph Regularized Low-rank Feature Learning for Robust Multi-Label Image Annotation. ICSP, 2016.

2015

  • Songhe Feng, Zheyun Feng, Rong Jin. Learning to Rank Image Tags with Limited Training Examples. IEEE Trans. on Image Processing,  24(4), pp. 1223-1234, 2015. (CCF A)
  • Chenjing Yan, Congyan Lang, Songhe Feng. Facial Age Estimation Based on Structured Low-rank Representation. ACM Multimedia, 2015. (CCF A)  
  • Xiaoyuan Luo^, Songhe Feng*. A General Method for Sensitive Identification Detection in the Terrorist Video. ICIMCS, 2015.
  • Tao Wang, Hua Yang, Congyan Lang, Songhe Feng. An Error-Tolerant Approximate Matching Algorithm for Labeled Combinational Maps. Neurocomputing, 156(25). pp. 211-220, 2015.

2014

  • Zheyun Feng, Songhe Feng, Rong Jin, A. K. Jain. Image Tag Completion by Noisy Matrix Recovery. ECCV, 2014. (CCF B)
  • Songhe Feng, Weihua Xiong. Hierarchical Sparse Representation based Multi-Instance Semi-Supervised Learning with Application to Image Categorization. Signal Processing, 94(1), pp.595-607, 2014.  

2013: 

  • Songhe Feng, Congyan Lang. Adaptive All-Season Image Tag Ranking by Saliency-Driven Image Pre-Classification. Journal of Visual Communication and Image Representation, 24(7),  pp.1031-1039. 2013. 
  • Congyan Lang, Songhe Feng. Supervised Sparse Patch Coding Towards Misalignment-Robust Face Recognition. Journal of Visual Communication and Image Representation, 24(2): 103-110, 2013. 

2012: 

  • Songhe Feng, Congyan Lang, Bing Li. Towards Relevance and Saliency Ranking of Image Tags. ACM Multimedia, 2012. (CCF A)  
  • Bing Li, Songhe Feng. Scaring or Pleasing: Exploit Emotional Impact of an Image. ACM Multimedia, 2012. (CCF A ) 

2011:  

  • Songhe Feng, Hong Bao. Combining Visual Attention Model with Multi-instance Learning for Tag Ranking. Neurocomputing, 74(2011). pp. 3619-3627. 
  • Songhe Feng, Congyan Lang. Combining Graph Learning and Region Saliency Analysis for Content-based Image Retrieval. Chinese Journal of Electronics, 39(10), pp. 2287-2294, 2011. (In Chinese)
  • Shuoyan Liu, De Xu, Songhe Feng. Region Contextual Visual Words for Scene Classification. Expert Systems with Applications, 11591-11597, 2011. 
  • Hong Bao, Songhe Feng. A Novel Saliency-based Graph Learning Framework with Application to CBIR. IEICE Trans. on Information System, 94(6), pp. 1353-1356, 2011.

2010:  

  • Songhe Feng, Congyan Lang, De Xu. Beyond Tag Relevance: Integrating Visual Attention Model and Multi-Instance Learning for Tag Saliency Ranking. ACM CIVR, 2010. (CCF B类)
  • Songhe Feng, De Xu. Transductive Multi-Instance Multi-Label Learning Algorithm with Application to Automatic Image Annotation. Expert Systems with Applications37(1), pp. 661-670, Jan.2010. 
  • Songhe Feng, De Xu. Attention-driven Salient Edge(s) and Region(s) Extraction with Application to CBIR. Signal Processing, 90(1), pp.1-15, 2010. 
  • Shuoyan Liu, De Xu, Songhe Feng. Discriminating Semantic Visual Words for Scene Classification. IEICE Trans. on Information System, 93(6), pp. 1580-1588, 2010.     

Earlier:

  • Songhe Feng, De Xu. Combining Attention Model with Hierarichical Graph Representation for Region-based Image Retrieval. IEICE Trans. on Information System, 91(8), pp. 2203-2206, 2008. 
  • Songhe Feng, De Xu. Automatic Image Annotation Using An Improved Multiple-Instance Learning Algorithm. Chinese Journal of Electronics, 17(1), pp. 43-47,2008. 
  • Songhe Feng, De Xu. Automatic Image Annotation using Semi-Supervised Multi-Instance Multi-Label Learning Algorithm. Chinese Journal of Electronics, 17(4), pp. 602-606, 2008. 
  • Songhe Feng, De Xu. A Novel Graph Kernel Based SVM Algorithm for Image Semantic Retrieval. ISNN, 2016.
  • Songhe Feng, De Xu. Locating Salient Edges for CBIR Based on Visual Attention Model. ICNC, 2006. 
  • Songhe Feng, De Xu. A Novel Region-based Image Retrieval Algorithm Using Selective Visual Attention Model. ACIVS, 2005.

教学工作

承担本科生课程:

  • C语言程序设计(詹天佑学院基础课程);    

承担研究生课程:

  • 机器视觉基础 (硕士生专业基础课程);
  • 视觉认知计算与图像语义计算 (博士生课程);

专利

  • 基于多子空间表示的偏多标记学习算法;专利号:202010412162.1
  • 基于全局和局部标记关系的偏多标记学习算法;专利号:202010411579.6
  • 特征信息存在噪声的偏多标记学习算法;专利号:202010411580.9;
  • 基于噪声容忍的偏多标记算法;专利号:202010412161.7;
  • 基于子空间表示和全局标记消歧的偏标记学习算法;专利号:202010397386.X;

获奖与荣誉

  • 2021年度,北京交通大学计算机学院师德师风先进个人(研途领航);
  • 2020年度,北京交通大学教书育人先进个人;
  • 2015年度,北京交通大学青年英才计划II类人选;
  • 2011年度,北京交通大学握奇奖教金;
  • 2010年度,北京交通大学计算机学院教学基本功比赛一等奖;

社会兼职

  • 北京市信息服务工程市重点实验室第三届学术委员会委员(2020-2022);
  • Senior Program Commitee Member: AAAI(2022);
  • Program Committee Member: NeurIPS(2021, 2022), ICML(2021), AAAI(2019, 2020, 2021), IJCAI(2019, 2020); 
  • Journal Reviewer for : IEEE Trans. on PAMI, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, IEEE Trans. on NNLS, IEEE Trans. on Cybernetics, IEEE Trans. on Big Data, ACM Trans. on Knowledg Discovery for Data, Knowledge-based Systems, Neurocomputing, Neural Networks;