梁孔明(Kongming Liang)

梁孔明 副研究员

梁孔明博士,北京邮电大学副研究员。2018年6月获得中国科学院计算技术研究所计算机应用方向博士学位,2019年至2021年于北京大学进行博士后阶段研究工作,主要研究方向为计算机视觉、深度学习和医学影像处理。以第一作者或通讯作者发表多篇国际会议期刊论文,其中包含国际顶级人工智能、计算机视觉与医学影像分析会议ICCV、AAAI、IJCAI、MICCAI等,以及机器学习顶级期刊TPAMI。共申请专利12项,其中授权2项。主持国家自然科学青年科学基金项目一项,作为算法负责人参与国家自然科学基金面上项目基于CT影像特征的肺栓塞人工智能辅助评估系统的创建与优化和北京市自然科学基金重点项目基于神经网络深度学习的脑卒中相关血管管壁斑块量化分析及破裂风险预警模型研究等课题研发。

电子邮箱: liangkongming AT bupt DOT edu DOT cn

研究方向:计算机视觉、深度学习和医学影像处理

招生信息

硕士、博士研究生: 学术型/专业型,欢迎保送/考研学生联系。请提前发送邮件预约面谈,附上简历和成绩单,其中博士研究生需要有较为独立的科研经历。

讲授课程

《Python编程与实践》、《医学影像分析技术前沿》

学术论文

期刊论文

  1. Shi, Zhao, C. Miao, U. Schoepf, R. H. Savage, D. M. Dargis, C. Pan, X. Chai, X. Li, S. Xia, X. Zhang, Yan Gu, Yonggang Zhang, B. Hu, Wenda Xu, C. Zhou, S. Luo, H. Wang, L. Mao, Kongming Liang, Li-li Wen, L. Zhou, Yizhou Yu, G. Lu and Long Jiang Zhang. “A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.” Nature Communications 11 (2020): n. pag.
  2. Kongming Liang, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen. Unifying Visual Attribute Learning with Object Recognition in a Multiplicative Framework, IEEE transactions on pattern analysis and machine intelligence 41.7 (2018): 1747-1760.
  3. Kongming Liang, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen. Visual Concept Conjunction Learning with Recurrent Neural Networks, Neurocomputing, 2019

会议论文

  1.  Zijin Yin, Kongming Liang*, Zhanyu Ma, and Jun Guo, Duplex Contextual Relation Network for Polyp Segmentation, in Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), 2022.
  2. Chenyu Guo, Jiyang Xie, Kongming Liang, Xian Sun, and Zhanyu Ma*, Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification, in Proceedings of ACM Multimedia Asia Conference, 2021.
  3. Kongming Liang, Kai Han, Xiuli Li, Xiaoqing Cheng, Yiming Li, Yizhou Wang, Yizhou Yu. Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images, MICCAI, 2021
  4. Chenghao Liu, Xiangzhu Zeng, Kongming Liang, Yizhou Yu, Chuyang Ye. Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects, MICCAI, 2021
  5. Shen Wang, Kongming Liang*, Yiming Li, Yizhou Yu, Yizhou Wang. Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation, International Conference on Medical Image Computing and Computer-Assisted Intervention, (2020, 208-217)
  6. Shen Wang*, Kongming Liang*, Chengwei Pan, Chuyang Ye, Xiuli Li, Feng Liu, Yizhou Yu, Yizhou Wang, Segmentation-based method combined with dynamic programming for brain midline delineation. The IEEE International Symposium on Biomedical Imaging (ISBI), 2020. [Accession number: 20202308795070]
  7. Chenghao Liu, Fengqian Pang, Yanlin Liu, Kongming Liang, Xiuli Li, Xiangzhu Zeng, Chuyang Ye. Semi-supervised brain lesion segmentation using training images with and without lesions. The IEEE International Symposium on Biomedical Imaging (ISBI), 2020.
  8. Quanhui Liu, Xiaoqing Cheng, Qirui Zhang, Changsheng Zhou, Xiuli Li, Shen Wang, Kongming Liang, Guangming Lu. Automatic Segmentation for Acute Ischemic Stroke from DWI Using Deep Convolutional Neural Networks. European Congress of Radiology (ECR). 2019
  9. Kongming Liang, Yuhong Guo, Hong Chang, Xilin Chen. Visual Relationship Detection with Deep Structural Ranking. AAAI Conference on Artificial Intelligence, 2018
  10. Kongming Liang, Yuhong Guo, Hong Chang, Xilin Chen. Incomplete Attribute Learning with auxiliary labels. IJCAI. 2017
  11. Kongming Liang, Hong Chang, Shiguang Shan, Xilin Chen. Attribute Conjunction Learning with Recurrent Neural Network. ECML. 2016
  12. Kongming Liang, Hong Chang, Shiguang Shan, Xilin Chen. A Unified Multiplicative Framework for Attribute Learning. Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2015
  13. Kongming Liang, Hong Chang, Zhen Cui, Shiguang Shan, Xilin Chen. Representation Learning with Smooth Autoencoder. ACCV. 2014.