(1)获奖情况 [1]2017年中国电子学会科技进步奖三等奖一项(排名第五); (2)教学/科研项目 [1]主持国家自然科学基金地区项目(62162033)“面向复杂多视图数据表示的深度矩阵/张量分解方法研究”; [2]主持国家自然科学基金青年项目(61603159)“面向低质量图像数据的稀疏低秩矩阵回归与分解方法研究”; [3]主持云南省基础研究计划面上项目(202101AT070438)“面向大规模复杂跨模态数据的语义表示与检索方法研究”; [4]主持云南省科技厅-新奥葡萄京“双一流”创建联合专项面上项目(202101BE070001-056)“基于稳健深度矩阵分解的肿瘤基因选择方法研究”; [5]主持2022年云南省“兴滇英才支持计划”青年人才项目“面向复杂大规模跨模态数据检索的哈希方法研究”; [6]主持江苏省自然科学基金青年项目(BK20160293)“基于稀疏低秩的鲁棒矩阵回归与分解方法研究”; [7]主持中国博士后科学基金项目(2017M611695)“基于稀疏低秩理论的图像回归与分解理论研究”; [8]主持江苏省博士后科学基金项目(1701094B)“面向高维图像鲁棒表示的稀疏低秩理论与方法研究”; [9]主持江苏省双创博士计划项目(科技副总类); [10]主持2017年江苏省社会安全图像与视频理解重点实验室开放课题(30916014107); (3)论文 [1]Zhenqiu Shu, et al. Dual local learning regularized NMF with sparse and orthogonal constraints.Applied Intelligence(SCI源刊), 2022. [2]Zhenqiu Shu, et al. Rank-constrained nonnegative matrix factorization algorithm for data representation. Information Sciences (SCI源刊), 2020, 528: 133-146. [3]Zhenqiu Shu, et al. Dual local learning regularized non-negative matrix factorization and its semi-supervised extension for clustering. Neural Computing and Applications (SCI源刊), 2021, 33(11): 6213-6231. [4] Zhenqiu Shu,et al. Spatial-spectral split attention residual network for Hyperspectral Image Classification. Journal of Selected Topics in Applied Earth Observations and Remote Sensing (SCI源刊 ), 2023, 16: 419-430.. [5]Zhenqiu Shu, et al. Correntropy-based dual graph regularized non-negative matrix factorization with Lp smoothness for data representation. Applied Intelligence (SCI源刊 ), 2022,52(7): 7653-7669. [6] Zhenqiu Shu, et al. Robust graph regularized NMF with dissimilarity and similarity constraints for scRNA-seq data clustering. Journal of Chemical Information and Modeling (SCI源刊),62(23):6271-6286. [7] Zhenqiu Shu, et al. Parameter-less auto-weighted multiple graph regularized nonnegative matrix factorization for data representation. Knowledge-based Systems (SCI源刊), 2017,131:105-112. [8] Zhenqiu Shu, et al. Local regularization concept factorization and its semi-supervised extension for image representation. Neurocomputing (SCI源刊), 2015, 152(22):1-12. [9] Zhenqiu Shu, et al. Structure preserving sparse coding for data representation. Neural Processing Letters (SCI源刊), 2018, 48 :1-15. [10]Zhenqiu Shu, et al. Local and global regularized sparse coding for data representation. Neurocomputing (SCI源刊), 2016, 198(29): 188-197. (4)知识产权 [1]舒振球等. 无参数自动加权多图正则化非负矩阵分解及图像识别方法. 发明专利,授权号:CN 107609596, 2020.(已授权) [2]舒振球等. 封顶概念分解方法及图像聚类方法. 发明专利,申请号:201711257431.6,2017.(已授权) [3]舒振球等. 面向多视图聚类的多图正则化深度矩阵分解方法. 发明专利,申请号:20180607971.0, 2018. (已授权) [4]舒振球等. 基于局部学习正则化的深度矩阵分解方法及图像聚类方法,发明专利,申请号:201810905948.X,2018. (已授权) 专著、教材 1、 2、 |