基本信息

 刘艳 计算机科学与技术学院
电子邮件:yanliu@ucas.ac.cn 

通信地址:北京市怀柔区怀北镇怀北庄中国科学院大学雁栖湖校区学园二383室

邮政编码:101408


研究领域

信号处理,图像处理,机器学习

研究兴趣

1. 信号处理
2. 图像处理
3. 机器学习

招生信息

   
招生专业
081203-计算机应用技术
招生方向
图像处理,信号处理,机器学习

教育背景

1、2007.6    中国科学院电子学研究所,信号与信息处理,博士学位

2、2004.6    山东大学信息科学与工程学院,通信与信息系统,硕士学位

3、2001.7    山东大学电子工程系,电子信息科学与技术,学士学位

   

出国学习工作

2013/12-2015/01,美国伊利诺伊大学香槟分校(UIUC),电子与计算机工程系,访问学者

工作经历


2013/12-2015/01,美国伊利诺伊大学香槟分校(UIUC),电子与计算机工程系,访问学者;
2007年7月至今   中国科学院大学 讲师,副教授。

教授课程

现代数字信号处理
数据库新技术
图像处理与计算机视觉
知识图谱的数据管理

出版信息

  • Contrastive Voxel Clustering for Functional and Structural Combined Brain Network Analysis: An fMRI-based study, Neuroimage, 2024, 297.

  • Fast 3D SAM: Crafting Large Vision Models for 3D Medical Image Segmentation via Token Clustering and Fine-tuning, ISBI'2024.

  •  A Multi-branch Attention-based Deep Learning Method for ALS Identification with sMRI Data, EMBC’2024.

  • Joint Analysis for Faciobrachial Dystonic Seizures Identiffcation in LGI1 Encephalitis using FDG-PET, CISP-BMEI’2024.

  • Biomarker Importance Analysis for Autoimmune Encephalitis with PET, CISP-BMEI’2024.

  • An Extensible Hierarchical Graph Convolutional Network for Early Alzheimer’s Disease Identification, Computer Methods and Programs in Biomedicine,2023, 238.

  • Role of Hippocampal Subfields in Neurodegenerative Disease Progression Analyzed With a Multi-scale Attention-based Network, NeuroImage: Clinical, 2023, 38.

  • Domain Contrast Network for cross-muscle ALS disease identification with EMG signal, Biomedical Signal Processing and Control, 2023, 82.

  • Voxel-level fMRI Analysis by Representation Learning and Deep Clustering for Alzheimer's Disease, ISBI’2023.

  • Selective ensemble learning for cross-muscle ALS disease identification with EMG signal, BIBM'2022.

  • A Multi-scale Attention-based Convolutional Network for Identification of Alzheimer’s Disease based on Hippocampal Subfields, EMBC’2022.

  • Gabor-based U-Net Crevasse Detection with Ground Penetrating Radar Data, GPR'2022.

  • Pulmonary Nodules Detection Assistant Platform: An Effective Computer Aided System for Early Pulmonary Nodules Detection in Physical Examination, Computer Methods and Programs in Biomedicine,2022, 217: 1-12.

  • Multi-resolution 3D-HOG Feature Learning Method for Alzheimer’s Disease Diagnosis, Computer Methods and Programs in Biomedicine, 2021, 214:1-8.

  • Shallow-Layers-Detection Ice Sounding Radar for Mapping of Polar Ice Sheets. IEEE Transactions on Geoscience and Remote Sensing, 2021, (99): 1-10.

  • Preliminary Investigation and Imaging Analysis of Early Lung Cancer Screening Among Petroleum Workers in North China, Cancer Investigation, 2021, 39(4): 321-332.

  • Efficient False Positive Reduction Method for Early Pulmonary Nodules Detection in Physical Examination, BIBM'2021.

  • Wavelet-based Multi-branch Convolutional Neural Network for Cross-individual ALS Disease Identification with EMG Signal, BIBM'2021.

  • Omics feature learning for cross individual ALS disease identification with EMG signal, BIBM'2021.

  • Analysis on Teeth Occlusion Distribution Based on Segmentation and Registration Algorithm, BIBM'2021.

  • Automated Classification of Alzheimer’s Disease and Mild Cognitive Impairment By Multi-scale Residual Neural Network in Hippocampus Subfields MR Images, RSNA’2021.

  • Automated Classification of Alzheimer’s Disease by Graph Convolutional network in Multi-modal MR Images, RSNA’2021.

  • Region-of-Interest Based Sparse Feature Learning Method for Alzheimer’s Disease Identification. Computer Methods and Programs in Biomedicine, 2020, 187: 1-10.

  • Gabor filter banks used for crevasse detection with Ground Penetrating Radar data, GPR’2020.

  • A Wrapper-based Feature Learning Method used for Alzheimer's disease Identification, ICSP2020.

  • Spatial Pyramid Based 3D Hog Feature Extraction for Alzheimer’s Disease Identification, ICSP2020.

  • Ice Crevasse Detection with Ground Penetrating Radar using Faster R-CNN, ICSP2020.

  • Automatic Sleep Stage Classification using Marginal Hilbert Spectrum Features and a Convolutional Neural Network, EMBC2020.

  • Comparison and Analyzation of Different Feature Parameters for Alzheimer’s disease Identification, EMBC'2019.

  • Tracing the Layer Boundary of the Ice Sheet from Radio-Echo Sounding Data, GPR’2018.

  • Compartmental Gaussian Mixture Model used for Layer Detection in Radio-Echo Sounding Data, ICSP’2018.

  • An Automatic Classification of Alzheimer’s Disease Based on Structural MRI Data Compared with Voxel-Based Morphometry Method. ISMRM’2018.

  • Automated Classification of Alzheimer’s Disease by Interregional Correlation Matrix in Structural MR Images. RSNA’2018.

  • Compartmental Sparse Feature Selection Method for Alzheimer’s disease Identification. EMBC’2017.  

  • Elastic Net based sparse feature learning and classification for Alzheimer’s disease identification. EMBC’2017.

  • Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and B0 Field Inhomogeneity, IEEE Transactions on Biomedical Engineering, 2016, vol.63, no.4, pp: 841-849.



科研项目

  • 医学人工智能创新单元,中央高校自主部署项目专项资金,2022.7-2024.12。

  • 多源融合学习的阿尔茨海默病辅助诊断方法研究,中央高校自主部署项目专项资金,2021.7-2023.12。

  • 基于深度学习技术的肺结节筛查软件开发项目,横向课题,2020.1-2020.12。

  • 冰裂隙检测雷达关键技术研究,国家自然基金面上项目,2018.1-2021.12

  • 极地高分辨率冰厚探测雷达成像与数据处理方法研究 ,国家自然科学基金青年基金,2014.1-2016.12 。

  • 《现代数字信号处理》课程,中科院十二五教育信息化“精品数字课程建设项目”,2012.12-2014.11。

  • 面向公共安全的智能视频监控新技术与新方法,北京市自然科学基金重点项目,2011.1-2013.12。