团队负责人
张重生
团队成员
张重生、侯彦娥、肖春静、凡高娟、Dr. Kamel Aouaidjia (师资博士后)、Dr. Muhammad Iran (师资博士后)、Dr. Zafar Samra (师资博士后)
研究方向
团队研究领域为:数据科学、人工智能。具体研究方向包括:(1)智能图像处理:含目标检测、识别、分割,动作识别与理解,文字识别,长尾学习等;(2)智能算法与时空优化;(3)图神经网络、时间序列异常检测;(4)人工智能与古文字前沿交叉领域;(5)人工智能物联网AIoT;(6)人工智能应用。
团队研究生培养和招新
研究生招生要求:1、在学术和科研方面有较高追求,热爱科研、喜欢钻研;2、性格沉稳,工作扎实,遵守纪律; 3、动手能力中等及以上,或学习成绩优异、且数学成绩较好。
代表性成果
科研项目
1.国家自然科学基金面上项目,基于机器学习的电动车辆路径问题优化算法研究,2025.01-2028.12,侯彦娥,主持,45万.
2.乐鱼app大巴黎赞助商部人文社会科学研究一般项目,“人工智能在西北汉简缀合中的应用研究”(23YJAZH210),张重生,主持,2023.10-2028.10.
3.国家社科基金重大项目“人机协同的甲骨分类缀合研究”(23&ZD309),张重生, (子)课题负责人,2023.12-2028.12.
4. 河南省科技攻关项目,“融入长尾学习与形似字辨识的高精度场景汉字识别技术”(232102211021),张重生,主持,2023.01-2024.12.
5. 河南省科技攻关项目,“基于WiFi信号的非阈值动作分割和自适应行为识别方法”,肖春静,主持,2021.1-2022.12.
论文著作
1. Chongsheng Zhang(张重生), Bin Wang, et al. Data-Driven Oracle Bone Rejoining: A Dataset and Practical Self-Supervised Learning Scheme [C]. SIGKDD 2022, pp. 4482-4492 (CCF-A顶级国际会议)
2. Chongsheng Zhang(张重生), Yaxin Hou, et al. Quality-Aware Self-Training on Differentiable Synthesis of Rare Relational Data [C]. AAAI 2023, pp. 6602-6611 (CCF-A顶级国际会议)
3. Chunjing Xiao(肖春静), et al. Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection [C], SIGKDD 2024. (CCF-A顶级国际会议)
4. Chunjing Xiao(肖春静), et al. Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models [C], SIGKDD 2023. (CCF-A顶级国际会议)
5. Chunjing Xiao(肖春静), et al. Counterfactual Graph Learning for Anomaly Detection on Attributed Networks [J]. IEEE Transactions on Knowledge and Data Engineering, 2023. (CCF-A类期刊).
6. Chunjing Xiao(肖春静), et al. Self-Supervised Few-Shot Time-series Segmentation for Activity Recognition. IEEE Transactions on Mobile Computing [J], 2023. (CCF-A类期刊).
7. Chunjing Xiao(肖春静), et al. Uncertainty-Aware Heterogeneous Representation Learning in POI Recommender Systems [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023. (IEEE汇刊, SCI 1区, IF: 8.7)
8. Chunjing Xiao(肖春静), et al. Mean Teacher-based Cross-Domain Activity Recognition using WiFi Signals [J]. IEEE Internet of Things Journal, 2023. (SCI 1区, IF: 10.6).
9. Yan-E Hou(侯彦娥), et al. Contextual Spatial-Channel Attention Network for Remote Sensing Scene Classification [J]. IEEE Geoscience and Remote Sensing Letters,2023. (SCI).
10. Yan-E Hou(侯彦娥), at al. A Deep Reinforcement Learning Real?Time Recommendation Model Based on Long and Short?Term Preference [J]. International Journal of Computational Intelligence Systems, 2023. (SCI).
11. Chongsheng Zhang(张重生), et al. Street View Text Recognition With Deep Learning for Urban Scene Understanding in Intelligent Transportation Systems [J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(7): 4727-4743. (IEEE汇刊, SCI 2区)
12. Aouaidjia Kamel, Bin Sheng, Ping Li, Jinman Kim, David Dagan Feng. Efficient Body Motion Quantification and Similarity Evaluation Using 3-D Joints Skeleton Coordinates [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(5): 2774-2788. (IEEE汇刊, SCI 1区)
13. Aouaidjia Kamel, Bin Sheng, Ping Li, Jinman Kim, David Dagan Feng. Hybrid Refinement-Correction Heatmaps for Human Pose Estimation [J]. IEEE Transactions on Multimedia, 2021, 23: 1330-1342. (IEEE汇刊, SCI 2区)
14. Gaojuan Fan(凡高娟), et al. SACA-UNet:Medical Image Segmentation Network Based on Self-Attention and ASPP [C]. IEEE CBMS 2023: 317-322
15. 多车型校车路径问题的优化算法研究 [M]. 侯彦娥. 河南大学出版社,2018.
16. 人工智能与深度学习实战 [M]. 张重生. 机械工业出版社. 2024.01.
17. 人工智能 人脸识别与搜索 [M]. 张重生. 电子工业出版社. 2020. 获国家出版基金资助.
18. 刷脸背后[M]. 张重生. 电子工业出版社. 2017.
19. 大数据分析:数据挖掘必备算法示例详解. 张重生. 机械工业出版社. 2016.
20. 深度学习:原理与实践[M]. 张重生. 电子工业出版社. 2016.
科研奖励
社会服务
其他成果
张重生作为特邀嘉宾和莫伯峰教授共同做客央视10套透视新科技栏目:
https://tv.cctv.com/2023/11/05/VIDEETfzfRLtgE4quaelIXAv231105.shtml