韩龙飞
博士，北京工商大学计算机学院，副教授
主要研究领域
计算机视觉、医学图像处理
联系方式
longfeihan@btbu.edu.cn
个人主页：
http://longfeihan.cn/LAB/
教育背景
2006.09 ~ 2010.06 郑州大学 信息与通信工程
2010.09 ~ 2012.06 北京理工大学 电子与信息工程
2012.09 ~ 2017.12 北京理工大学 信息与通信工程
2015.09 ~ 2017.06 卡内基梅隆大学 机器人系访学
工作经历
2018.01 ~ 2021.05 腾讯科技有限公司 高级工程师
2022.03 ~ 至今 中国科学技术大学 博士后
科研项目
[1] 主持国家自然科学基金青年项目，基于跨域知识迁移的多源异质联邦推荐方法研究，2023-2025.
[2] 主持北京市教委科研计划一般项目，面向图像敏感内容的智能检索技术研究，2023-2025.
[3] 主持神经网络硬件加速器自动化测试软件开发项目，2022-2023.
[4] 承担安徽省高校协同创新项目，多模态内窥镜成像数据的多元属性获取与知识推理，2022-2024.
[5] 承担安徽省重点研发项目，多模态智能成像内窥镜的研发及其在消化道疾病诊断中的示范应用，2023-2026.
学术兼职
担任中国人工智能学会青工委会员；
期刊审稿人：IEEE Transactions on Cognitive and Developmental Systems (IEEE TCDS), IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), IEEE Transactions on Circuits and Systems for Video Technology (IEEE CSVT)等。
发表论文：
[1] Dong X(*), Han L(*), Zhang D, Liu L, Han J, Zhang H. Giving Text More Imagination Space for Image-text Matching. In Proceedings of the 31st ACM International Conference on Multi-media (ACM MM), 2023, Accepted. CCF A类会议
[2] Huang G, Yao J, Huang P, Han L(*). A Mutual Enhancement Framework for Specular Highlight Detection and Removal. Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2023, Accepted. CCF C类会议
[3] Cheng P, Huang P, Xu C, Han L(*). Region Guided Transformer for Single Image Raindrop Removal. In Proceedings of 7th Asian Conference on Artificial Intelligence Technology (ACAIT), 2023, Accepted. EI会议
[4] Wang Q, Huang P, Li L, Han L(*). WATNet: A wavelet-aware Lightweight Hybrid Model for Fast Low-Light Enhancement. In Proceedings of 7th Asian Conference on Artificial Intelligence Technology (ACAIT), 2023, Accepted. EI会议
[5] Qin H, Han L, Xiong W, Wang J, Ma W, Li B, Hu W. Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, 2023. CCF A类会议
[6] Xu C, Wang Y, Zhang D, Han L(*), Zhang Y, Chen J, Li S. BMAnet: Boundary Mining with Adversarial Learning for Semi-supervised 2D Myocardial Infarction Segmentation[J]. IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023, 27(1): 87-96. 中科院1区
[7] Qin H, Han L, Wang J, Zhang C, Li Y, Li B, Hu W. Attention-aware Learning for Hyperparameter Prediction in Image Processing Pipelines[C], European Conference on Computer Vision (ECCV), 2022. CCF B类会议
[8] Fan Y, Han L(*), Zhang Y, et al. Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction[C]. ACM MM Workshop HCMA, 2022. EI会议
[9] Hu Y, Luo S, Han L, Pan L, Zhang T. Deep supervised learning with mixture of neural networks[J]. Artificial intelligence in medicine, 2020, 102: 101764. 中科院2区
[10] Han L, Zhang D, Huang D, Chang X, Ren J, Luo S, Han J. self-paced mixture of regressions[C]. International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Austrilia, 2017. CCF A类会议
[11] Huang D, Han L, Fernando de la Torre. Soft-margin mixture of regressions[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, 2017. CCF A类会议
[12] Han L, Luo S, Yu J, Pan L, Chen S. Rule Extraction from Support Vector Machines Using Ensemble Learning Approach: An Application for Diagnosis of Diabetes[J]. IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI), 2015, 19(2): 728-734. 中科院1区
[13] Han L, Luo S, Wang H, Pan L, Ma X, Zhang T. An Intelligible Risk Stratification Model for Diabetes based on Semi-supervised Clustering[J]. IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI), 2017, 21(5): 1288-1296. 中科院1区
Longfei Han, Ph.D., Sc
hool of Computer Science and Engineering, Beijing Technology and Business University, Associate Professor
Research Interests:
Computer Vision, medical image analysis
Contact:
Personal Website:
http://longfeihan.cn/LAB/
Education:
2006.09 ~ 2010.06 Zhengzhou University, School of Information and Electronics
2010.09 ~ 2012.06 Beijing Institute of Technology, School of Information and Electronics
2012.09 ~ 2017.12 Beijing Institute of Technology, School of Information and Electronics
2015.09 ~ 2017.06 Carnegie Mellon University, Robotics Institute
Work Experiences:
2018.01 ~ 2021.05 Tencent, Senior Engineer
Publications:
[1] Dong X(*), Han L(*), Zhang D, Liu L, Han J, Zhang H. Giving Text More Imagination Space for Image-text Matching. In Proceedings of the 31st ACM International Conference on Multi-media (ACM MM), 2023, Accepted.
[2] Huang G, Yao J, Huang P, Han L(*). A Mutual Enhancement Framework for Specular Highlight Detection and Removal. Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2023, Accepted.
[3] Cheng P, Huang P, Xu C, Han L(*). Region Guided Transformer for Single Image Raindrop Removal. In Proceedings of 7th Asian Conference on Artificial Intelligence Technology (ACAIT), 2023, Accepted.
[4] Wang Q, Huang P, Li L, Han L(*). WATNet: A wavelet-aware Lightweight Hybrid Model for Fast Low-Light Enhancement. In Proceedings of 7th Asian Conference on Artificial Intelligence Technology (ACAIT), 2023, Accepted.
[5] Qin H, Han L, Xiong W, Wang J, Ma W, Li B, Hu W. Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, 2023.
[6] Xu C, Wang Y, Zhang D, Han L(*), Zhang Y, Chen J, Li S. BMAnet: Boundary Mining with Adversarial Learning for Semi-supervised 2D Myocardial Infarction Segmentation[J]. IEEE Journal of Biomedical and Health Informatics (IEEE JBHI), 2023, 27(1): 87-96.
[7] Qin H, Han L, Wang J, Zhang C, Li Y, Li B, Hu W. Attention-aware Learning for Hyperparameter Prediction in Image Processing Pipelines[C], European Conference on Computer Vision (ECCV), 2022.
[8] Fan Y, Han L(*), Zhang Y, et al. Dual Domain-Adversarial Learning for Audio-Visual Saliency Prediction[C]. ACM MM Workshop HCMA, 2022.
[9] Hu Y, Luo S, Han L, Pan L, Zhang T. Deep supervised learning with mixture of neural networks[J]. Artificial intelligence in medicine, 2020, 102: 101764.
[10] Han L, Zhang D, Huang D, Chang X, Ren J, Luo S, Han J. self-paced mixture of regressions[C]. International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Austrilia, 2017.
[11] Huang D, Han L, Fernando de la Torre. Soft-margin mixture of regressions[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, 2017.
[12] Han L, Luo S, Yu J, Pan L, Chen S. Rule Extraction from Support Vector Machines Using Ensemble Learning Approach: An Application for Diagnosis of Diabetes[J]. IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI), 2015, 19(2): 728-734.
[13] Han L, Luo S, Wang H, Pan L, Ma X, Zhang T. An Intelligible Risk Stratification Model for Diabetes based on Semi-supervised Clustering[J]. IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI), 2017, 21(5): 1288-1296.