后续待更新

主持国家重点研发计划课题、国家自然科学基金、北京市自然科学基金项目、北京市科技人才交叉项目等国家、省部级项目。

1) 国家重点研发计划项目课题,城市道路地下病害体智能识别与精准解释技术研究,2022.02-2025.01, 负责人.

2) 国家自然科学基金面上项目,排水管道智能视觉感知中少样本学习和可解释性建模研究,2022.01-2025.12, 负责人.

3) 国家自然科学基金青年项目,基于深度时空轨迹特征的复杂场景人体行为识别,2017.01-2019.12, 负责人.

4) 北京市自然科学基金面上项目,面向城市安全的排水管道内部缺陷智能识别和三维重建视觉方法研究,2020.01-2022.12,负责人.

5) 北京市科技新星计划支持项目,北京市政排水管线内部缺陷检测与三维可视化方法研究,2019.11-2022.10,负责人.

6) 北京市科技新星交叉项目,面向5G网络的城市道路地下排水管道周围病害体智能识别系统研究,2021.11-2024.10, 负责人.

7) 国家自然科学基金面上项目,面向端计算的深度网络结构搜索与进化,2020.01-2024.12, 17万元,合作单位负责人.

8) 国家自然科学基金面上项目,基于智能安防时空情境理解的异常事件高效解析方法研究, 2019.01-2023.12, 12.025万元, 合作单位负责人.

9) 北京市科技新星交叉项目, 基于生成式AI的高比例可再生能源综合微网韧性调度优化技术,2025.07-2028.06,合作单位负责人.

1）著作

[1] 李策,彭苏萍,杨峰,乔旭,闫睿. 排水管道机器人智能视觉探测原理及应用, 哈尔滨工业大学出版社, 2024.

[2] Baochang Zhang, Ce Li, Nana Lin. Machine Learning and Visual perception, De Gruyter, 2020.

[3] 焦建彬,叶齐祥,韩振军,李策.视觉目标检测与跟踪,科学出版社, 2016.

2）论文

[1] Ce Li, et. al. (2021). Memory attention networks for skeleton-based action recognition. IEEE Transactions on Neural Networks and Learning Systems, 33(9), 4800-4814.

[2] Ce Li, et. al. (2019). Deep manifold structure transfer for action recognition. IEEE Transactions on Image Processing, 28(9), 4646-4658.

[3] Ce Li, et. al. (2018). Deep fisher discriminant learning for mobile hand gesture recognition. Pattern Recognition, 77:276-288.

[4] Ce Li, et. al. (2024). Multi-scale adaptive feature network drainage pipe image dehazing method based on multiple attention. Electronics, 13(7), 1406.

[5] Ce Li, et. al. (2024). Intelligent analysis system for teaching and learning cognitive engagement based on computer vision in an immersive virtual reality environment. Applied Sciences, 14(8), 3149.

[6] Ce Li, et. al. (2019). Pipeline Defect Detection Cloud System Using Role Encryption and Hybrid Information. Computers, Materials & Continua, 61(3).

[7] Ce Li, et. al. (2019). Tunnel crack detection using coarse‐to‐fine region localization and edge detection. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(5), e1308.

[8] Ce Li, et. al. (2019). Enhanced bird detection from low-resolution aerial image using deep neural networks. Neural Processing Letters, 49, 1021-1039.

[9] Ce Li, et. al. (2013). Visual abnormal behavior detection based on trajectory sparse reconstruction analysis. Neurocomputing, 119, 94-100.

[10] Ce Li, et. al. (2018). Robust kernelized correlation filter with scale adaption for real-time single object tracking. Journal of Real-Time Image Processing, 15(3): 583-596.

[11] Linlin Yang^#, Ce Li^#, et. al. (2017). Image reconstruction via manifold constrained convolutional sparse coding for image sets, IEEE Journal of Selected Topics in Signal Processing, 11(7):1072-1081.

[12] Chunyu Xie, Ce Li, et. al. (2019). Hierarchical residual stochastic networks for time series recognition. Information Sciences, 471, 52-63.

[13] Hongren Wang, Ce Li, et. al. (2019). Gaussian transfer convolutional neural networks. IEEE Transactions on Emerging Topics in Computational Intelligence, 3(5), 360-368.

[14] Longshuai Sheng, Ce Li*. (2023). Weakly supervised coarse-to-fine learning for human action segmentation in HCI videos, Multimedia Tools and Applications, 82(9):12977-12993.

[15] Shan Gao, Zhenjun Han, Ce Li, et. al. (2015). Real-time multi-pedestrian tracking in traffic scenes via an RGB-D-based layered graph model. IEEE Transactions on Intelligent Transportation Systems, 16(5), 2814-2825.

[16] Fukai Zhang, Ce Li, et. al. (2019).Vehicle detection in urban traffic surveillance images based on convolutional neural networks with feature concatenation. Sensors, 19(3):594.

[17] Baochang Zhang, Alessandro Perina, Ce Li, et. al. (2018). Manifold constraint transfer for visual structure-driven optimization. Pattern Recognition, 77:87-98.

[18] Linlin Yang, Ce Li, et. al. (2018). Adaptive multiclass correlation filters and its applications in recognition. Journal of Electronic Imaging, 27(3):033010.

[19] Pinjie Xu, Ce Li*, et. al. (2019). Underground disease detection based on cloud computing and attention region neural network. Journal of Artificial Intelligence, 1(1):9-18.

[20] Qian Liu, Feng Yang, Ce Li. (2019). AWBING plus algorithm for generic object proposal generation. Journal of Intelligent & Fuzzy Systems, 36(6), 6685-6701.

[21] Jiaxin Gu^#, Ce Li^#, et. al. (2019, July). Projection convolutional neural networks for 1-bit cnns via discrete back propagation. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).

[22] Chunyu^#, Ce Li^#, et. al. (2018, January). Memory attention networks for skeleton-based action recognition, In 2018 International Joint Conference on Artificial Intelligence (IJCAI).

[23] Xiaodi Wang, Baochang Zhang, Ce Li, et. al. (2018, June). Modulated convolutional networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[24] Ce Li, et. al. (2016, March). Cluster-based dictionary learning and locality-constrained sparse reconstruction for trajectory classification. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE.

[25] Ce Li, et. al. (2014, August). Locality-constrained Sparse Reconstruction for Trajectory Classification. In 2014 22nd International Conference on Pattern Recognition (ICPR), IEEE.

[26] Ce Li, et. al. (2017, November). Evaluation of super-resolution on bird detection performance based on deep convolutional networks. In 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[27] Ce Li, et. al. (2025, July). 2s-TAS: Two-stream transformer for multi-modal human action segmentation. In 2025 IEEE International Conference on Multimedia and Expo (ICME).

[28] Ce Li, et. al. (2025, July).Improved pipeline disease grading detection method for visual inspection of sewer pipeline robots. In 2025 IEEE International Conference on Multimedia and Expo (ICME).

[29] Ce Li, et. al. (2011, August). Abnormal behavior detection via sparse reconstruction analysis of trajectory. In 2011 Sixth International Conference on Image and Graphics (ICIG).

[30] Ce Li, et. al. (2023, November). Improved sliding window smoothing for video temporal action segmentation and recognition. In 2023 China Automation Congress (CAC) (pp. 8653-8658). IEEE.

[31] Yujia Chen, Ce Li*. (2017, November). GM-Net: Learning features with more efficiency. In 2017 4th IAPR Asian Conference on Pattern Recognition (ACPR).

[32] Tingran Wang, Ce Li*, et. al. (2022, December). High-Fidelity Pluralistic Image Completion with PLSA-VQGAN. In 2022 International Conference on High Performance Big Data and Intelligent Systems (HDIS).

[33] Qin Han, Ce Li*, et. al. (2023, November). Pipeline Inner Surface 3D Reconstruction and Depth Prediction Based on Fast-MVSNet for Intelligent Sewer Robot Vision. In 2023 China Automation Congress (CAC).

[34] Shan Gao, Zhenjun Han, Ce Li, et. al. (2013, December). Real-time multi-pedestrian tracking based on vision and depth information fusion. In Advances in Multimedia Information Processing–PCM 2013: 14th Pacific-Rim Conference on Multimedia (PCM).

[35] Xingchao Liu, Ce Li, et. al. (2019, January). Starts Better and Ends Better: A Target Adaptive Image Signature Tracker. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

[36] Xiaodi Wang, Ce Li, et. al. (2019, January). Taylor Convolutional Networks for Image Classification. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

[37] 杨超宇，李策，等. 基于视频的煤矿安全监控行为识别系统研究[J].煤炭工程,2016,48(04):111-113+117.

[38] 杨超宇，李策，等. 基于改进粒子滤波的煤矿视频监控模糊目标检测[J].吉林大学学报(工学版),2017,47(06):1976-1985.

[39] 李涛涛，李策*，等.基于嵌入式以太网的地质雷达通信系统的研究[J]. 煤炭技术,2017,36(03):242-245.

[40] 李策.炮弹发射弹道命中目标误差校正估计仿真[J].计算机仿真,2017,34(03):15-18.

[41] 王丽珍，胡天睿，李策*. 基于LCSCA特征与协同表示的轨迹分析算法[J].济南大学学报(自然科学版),2017,31(03):202-207.

[42] 李涛涛，杨峰，李策，等. 基于光条信度评价的线结构光传感器曝光时间优化[J].光学学报,2018,38(01):184-192.

[43] 苏剑臣，李策*，等. 基于边缘帧差和高斯混合模型的行人目标检测[J].计算机应用研究,2018,35(04):1246-1249.

[44] 李策，等. 基于RGM色彩空间的色盲矫正方法. 计算机应用研究，35（12），2018.

[45] 刘倩, 李策，等. 基于似物目标的快速行人检测算法[J].计算机应用研究,2019,36(07):2219-2222.

[46] 刘倩, 李策*，等. 加权极限学习机在行人检测中的研究和应用[J].计算机工程与设计,2019,40(08):2366-2371.

[47] 张富凯,杨峰,李策.基于改进YOLOv3的快速车辆检测方法[J].计算机工程与应用,2019,55(02):12-20.

[48] 盛龙帅, 李策*，等. 基于注意力机制的乳腺X线摄影分类方法[J].计算机工程与应用,2020,56(08):166-170.

[49] 徐频捷，王诲喆，李策*，等. 基于脉冲神经网络与移动GPU计算的图像分类算法研究与实现[J]. 计算机工程与科学，2020.

3）专利

[1] Ce Li, et. al. Method for rapidly dehazing underground pipeline image based on dark channel prior, United States, US11,145,035 B2, 2021.

[2] Ce Li, et. al. Weakly supervised learning based method for recognizing behavior through video segmentation, Nederland, N2029182, 2023.

[3] Ce Li, et. al. Method for restoring video data of drainage pipe based on computer vision, United States, US11,620,735 B2, 2023.

[4] 李策,等.一种基于图卷积神经网络的骨架数据行为识别方法,中国, ZL201910499246.0, 2020.

[5] 李策, 等. 基于暗通道与Retinex的地下管道图像去雾方法,中国, ZL 202110207398.6, 2022.

[6] 李策, 等. 一种破损圆柱形排水管道内壁三维重建方法,中国, ZL201810377499.6, 2019.

[7] 李策, 等. 一种基于改进的卷积匹配追踪管道视频图像去雾增强方法,中国, ZL201811026306.9, 2019.

[8] 李策, 等.一种基于计算机视觉与机器学习的管道缺陷识别方法,中国, ZL201910136101.4, 2019.

[9] 李策, 等.一种结合边缘帧差和高斯混合模型的运动目标检测方法,中国,ZL201710678856.8, 2018.

[10] 李策, 等. 基于深度卷积神经网络的雷达信号铁路路基病害检测方法,中国, ZL 201710928460.4, 2018.

[11] 李策, 等. 一种基于全局特征和稀疏表示分类的人体行为识别方法,中国,ZL 201711111597.7,2018.

[12] 李策，等. 一种排水管道单目视频三维重建和深度预测方法，中国，ZL 2024 1 0129446.8, 2025.

获北京市科技新星、越崎青年学者、教书育人先锋、龙软科技教师贡献奖、北京图象图形学会最美女科技工作者等荣誉。获教育部高等学校科学研究优秀成果奖二等奖（序1）、北京市科学技术奖二等奖（序3）、河南省科学技术奖一等奖（序5）、中国产学研合作创新成果优秀奖（序1）、中国发明协会年度发明创业奖人物奖。带领团队获北京市大学生科技创新成果展示创新金奖、北京市互联网+大学生创新创业大赛一等奖 、北京市挑战杯大学生课外学术科技作品竞赛一等奖等。