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[1] Qi Zhu, Huijie Li, Haizhou Ye, Zhiqiang Zhang, Ran Wang, Zizhu Fan, Daoqiang Zhang. Incomplete Multi-Modal Brain Image Fusion for Epilepsy Classification. Information Sciences, 2021 （SCI）
[2] Qi Zhu, Jing Yang, Bingliang Xu, Zhenghua Hou, Liang Sun, Daoqiang Zhang. Multimodal Brain Network Jointly Construction and Fusion for Diagnosis of Epilepsy. Frontiers in Neuroscience, 1121 （SCI）
[3] Rui Zhang, Qi Zhu,, Xiangyu Xu, Daoqiang Zhang, Sheng-Jun Huang. Visual-guided attentive attributes embedding for zero-shot learning. Neural Networks, 2021, 143: 709--718 （SCI）
[4] Kai Ma, Wei Shao, Qi Zhu, Daoqiang Zhang. Kernel based statistic: Identifying topological differences in brain networks. Intelligent Medicine, 2021
[5] Geng Zhang, Qi Zhu, Jing Yang, Ruting Xu, Zhiqiang Zhang, Daoqiang Zhang. Functional Brain Connectivity Hyper-Network Embedded with Structural Information for Epilepsy Diagnosis. International Journal of Image and Graphics, 2021: 2250029 （EI）
[6] Nuoya Xu, Qi Zhu, Xiangyu Xu, Daoqiang Zhang. An effective recognition approach for contactless palmprint. The Visual Computer, 123,94-107(2020) （SCI）
[7] Qi Zhu, Xiangyu Xu, Ning Yuan, Zheng Zhang, Donghai Guan, Shengjun Huang, Daoqiang Zhang. Latent correlation embedded discriminative multi-modal data fusion. Signal Processing, 2020, 171: 107466 （SCI）
[8] Qi Zhu, Rui Zhang, Sheng-Jun Huang, Zheng Zhang, Daoqiang Zhang. LGSLRR: Towards fusing discriminative ordinal local and global structured low-rank representation for image recognition. INFORMATION SCIENCES, 539(2020) 522-535 （SCI）
[9] Zhang Zheng, Qi Zhu, Xie Guosen, Chen Yi, Li Zhengming, Wang Shuihua. Discriminative margin-sensitive autoencoder for collective multi-view disease analysis. Neural Networks, 2020, 123: 94--107 （SCI）
[10] Qi Zhu, Nuoya Xu, Shengjun Huang, Jianjun Qian, Daoqiang Zhang. Adaptive feature weighting for robust Lp-norm sparse representation with application to biometric image classification. International Journal of Machine Learning and Cybernetics, 2020, 11(2): 463--474 （SCI）
[11] Jiashuang Huang, Qi Zhu, Mingliang Wang, Luping Zhou, Zhiqiang Zhang, Daoqiang Zhang. Coherent Pattern in Multi-layer Brain Networks: Application to Epilepsy Identification. IEEE Journal of Biomedical and Health Informatics, 2020: 1--12 （SCI）
[12] Qi Zhu, Nuoya Xu, Zheng Zhang, Donghai Guan, Ran Wang, Daoqiang Zhang. Cross-spectral palmprint recognition with low-rank canonical correlation analysis. Multimedia Tools and Applications, 2019: 1--22（SCI）
[13] Zhu Qi, Yuan Ning, Huang Jiashuang, Hao Xiaoke, Zhang Daoqiang. Multi-modal AD classification via self-paced latent correlation analysis. Neurocomputing, 2019, 355: 143--154（SCI）
[14] Qi Zhu, Ning Yuan, Donghai Guan, Nuoya Xu, Huijie Li. An alternative to face image representation and classification. International Journal of Machine Learning and Cybernetics, 2019, 10(7): 1581--1589（SCI）
[15] Qi Zhu, Huijie Li, Jiashuang Huang, Xijia Xu, Donghai Guan, Daoqiang Zhang. Hybrid Functional Brain Network With First-Order and Second-Order Information for Computer-Aided Diagnosis of Schizophrenia. Frontiers in Neuroscience, 2019, 13: 603（SCI）
[16] Qi Zhu, Ning Yuan,, Donghai Guan. Cognitive Driven Multilayer Self-Paced Learning with Misclassified Samples. Complexity, 2019, （SCI）
[17] Jinrong Cui, Qi Zhu, Ding Wang, Zuoyong Li. Learning Robust Latent Representation for Discriminative Regression. Pattern Recognition Letters, 2019, 117: 193--200（SCI）
[18] Jiashuang Huang, Qi Zhu, Xiaoke Hao, Xiaomeng Shi, Shuzhan Gao, Xijia Xu, Daoqiang Zhang. Identifying Resting-State Multifrequency Biomarkers via Tree-Guided Group Sparse Learning for Schizophrenia Classification. IEEE Journal of Biomedical and Health Informatics, 2019, 23(1): 342--350（SCI）
[19] 张道强, 朱旗, 郝小可, 邵伟, 王明亮, 黄嘉爽, 黄硕. 脑影像智能分析. 中国科学：信息科学
[20] 朱旗, 黄嘉爽, 郝小可, 张道强. 基于脑影像智能分析的阿尔茨海默病辅助诊断. 人工智能学会通讯, 2018年1期
[21] Qi Zhu, Jiuwen Zhu, Mingxia Liu, Xijia Xu, Daoqiang Zhang. Multi-Region Correlation Based Functional Brain Network for Disease Diagnosis and Cognitive States Detection. IEEE Access, 2018, 6: 78065--78076（SCI）
[22] Qi Zhu, Jiashuang Huang, Xijia Xu. Non-negative discriminative brain functional connectivity for identifying schizophrenia on resting-state fMRI. Biomedical Engineering Online, 2018, 17(1): 32--32（SCI）
[23] Weiwei Yuan, Donghai Guan, Qi Zhu, Tinghuai Ma. Novel mislabeled training data detection algorithm. Neural Computing and Applications, 2018, 29(10): 673--683（SCI）
[24] Zizhu Fan, Da Zhang, Xin Wang, Qi Zhu, Yuanfang Wang. Virtual dictionary based kernel sparse representation for face recognition. Pattern Recognition, 2018, 76: 1--13（SCI）
[25] Dan Zhang, Qi Zhu, Daoqiang Zhang. Multi-modal dimensionality reduction using effective distance. Neurocomputing, 2017, 259: 130--139（SCI）
[26] Jin-Xing Liu, Yong Xu, Ying-Lian Gao, Chun-Hou Zheng, Dong Wang, Qi Zhu. A Class-Information-Based Sparse Component Analysis Method to Identify Differentially Expressed Genes on RNA-Seq Data. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016, 13(2): 392-398（SCI）
[27] Qi Zhu, Zheng Zhang, Ningzhong Liu, Han Sun. Near infrared hand vein image acquisition and ROI extraction algorithm. Optik, 2015, 126(24): 5682--5687
[28] Qingxiang Feng, Qi Zhu, Linlin Tang, Jengshyang Pan. Robust coarse-to-fine face recognition method. Optik, 2015, 126(23): 4159--4165（SCI）
[29] Qingxiang Feng, Qi Zhu, Linlin Tang, Jengshyang Pan. L1-norm plus L2-norm sparse parameter for image recognition. Optik, 2015, 126(23): 4078--4082（SCI）
[30] Qi Zhu, Ningzhong Liu, Zheng Zhang, Baisheng Dai. Multi-Sample Sparse Representation for Robust Face Recognition. Journal of Computational and Theoretical Nanoscience, 2015, 12(11): 4166--4178
[31] Yuwu Lu, Zhihui Lai, Zizhu Fan, Jinrong Cui, Qi Zhu. Manifold discriminant regression learning for image classification. Neurocomputing, 2015, 166: 475--486（SCI）
[32] Zheng Zhang, Long Wang, Qi Zhu, Shukai Chen, Yan Chen. Pose-invariant face recognition using facial landmarks and Weber local descriptor. Knowledge Based Systems, 2015, 84: 78--88（SCI）
[33] Zizhu Fan, Ming Ni, Qi Zhu, Ergen Liu. Weighted sparse representation for face recognition. Neurocomputing, 2015, 151(mar.3pt.1): 304-309（SCI）
[34] Zheng Zhang, Long Wang, Qi Zhu, Zhonghua Liu, Yan Chen. Noise modeling and representation based classification methods for face recognition. Neurocomputing, 2015, 148: 420-429（SCI）
[35] Qi Zhu, Daoqiang Zhang, Han Sun, Zhengming Li. Combining L1-norm and L2-norm based sparse representations for face recognition. Optik - International Journal for Light and Electron Optics, 2015, 126(7-8): 719-724（SCI）
[36] Qi Zhu, Jin Rong Cui, Zi Zhu Fan. Matrix Based Feature Measurement and Extraction for Face Recognition. Applied Mechanics & Materials, 2015, 738-739: 643-647 2014（SCI）
[37] Qingxiang Feng, Qi Zhu, Lin-Lin Tang, Jeng-Shyang Pan. Double linear regression classification for face recognition. Journal of Modern Optics （SCI）
[38] Qi Zhu, Han Sun, Qingxiang Feng, Jinghua Wang. CCEDA: building bridge between subspace projection learning and sparse representation-based classification. Electronics Letters, 2014, 50(25): 1919-1921（SCI）
[39] Yuyao Wang, Qi Zhu, Yan Chen, Min Wang. A novel virtual samples-based sparse representation method for face recognition. optik:=Journal for Light-and Electronoptic, 2014（SCI）
[40] Yong Xu, Xiaozhao Fang, Qi Zhu, Yan Chen, Jane You, Hong Liu. Modified minimum squared error algorithm for robust classification and face recognition experiments. Neurocomputing, 2014, 135(jul.5): 253–261（SCI）
[41] Xuxin Gu, Jinrong Cui, Qi Zhu. Abnormal crowd behavior detection by using the particle entropy. Optik - International Journal for Light and Electron Optics, 2014, 125(14): 3428-3433（SCI）
[42] Chengli Sun, Qi Zhu, Minghua Wan. A novel speech enhancement method based on constrained low-rank and sparse matrix decomposition. Speech Communication, 2014, 60: 44-55
[43] Minna Qiu, Zhengming Li, Yaowu Wang, Qi Zhu. The comparative analysis l2-minimisation based description methods. Optik - International Journal for Light and Electron Optics, 2014, 125(1): 374-379（SCI）
[44] Qi Zhu, Yong Xu, Yuwu Lu, Jiajun Wen, Zhengming Li. Novel Matrix Based Feature Extraction Method for Face Recognition Using Gaborface Features. Advances in Intelligent Systems and Computing, 2014, 238: 349-357（SCI）
[45] Yong Xu, Qi Zhu, Yan Chen, Jeng-Shyang Pan. An improvement to the nearest neighbor classifier and face recognition experiments. Int. J. Innov. Comput. Inf. Control（SCI）
[46] Xingjie Zhu, Yong Xu, Huaiyou Chen, Yan Liu, Jiajun Wen, Qi Zhu. Low false reject rate and false accept rate multi-step fire detection method. Optik - International Journal for Light and Electron Optics, 2013, 124(24): 6636-6641（SCI）
[47] Xiaolong Wang, Qi Zhu, Jinrong Cui, Yuewu Wang. Sparse representation method based on Gabor and CLBP. Optik - International Journal for Light and Electron Optics, 2013, 124(22): 5843-5850（SCI）
[48] Zizhu Fan, Jinghua Wang, Qi Zhu, Xiaozhao Fang, Jinrong Cui, Chunhua Li. Local minimum squared error for face and handwritten character recognition. Journal of electronic imaging, 2013, 22(3): 033027.1-033027.9（SCI）
[49] Qi Zhu, Chengli Sun. Image-based face verification and experiments. Neural Computing and Applications, 2013, 23(3-4): 947-956（SCI）
[50] Qi Zhu, Zhengming Li, Jinxing Liu, Zizhu Fan, Lei Yu, Yan Chen. Improved Minimum Squared Error Algorithm with Applications to Face Recognition. PLOS ONE, 2013, 8(8)（SCI）
[51] Yong Xu, Qi Zhu, Zizhu Fan, Yaowu Wang, Jeng Shyang Pan. From the idea of "sparse representation" to a representation-based transformation method for feature extraction. Neurocomputing, 2013, 113(aug.3): 168-176（SCI）
[52] Zhengming Li, Qi Zhu, Binglei Xie, Jian Cao, Jin Zhang. A Collaborative Neighbor Representation Based Face Recognition Algorithm. Mathematical Problems in Engineering, 2013, 2013: 1--9（SCI）
[53] Yong Xu, Qi Zhu, Zizhu Fan, David Zhang, Jianxun Mi, Zhihui Lai. Using the idea of the sparse representation to perform coarse-to-fine face recognition. Information Sciences, 2013, 238: 138--148（SCI）
[54] Yong Xu, Qi Zhu, Zizhu Fan, Minna Qiu, Yan Chen, Hong Liu. Coarse to fine K nearest neighbor classifier. Pattern Recognition Letters, 2013, 34(9): 980-986（SCI）
[55] Yong Xu, Qi Zhu. A simple and fast representation-based face recognition method. Neural Computing and Applications, 2013, 22(7-8): 1543-1549（SCI）
[56] Qi Zhu, Yong Xu. Multi-directional two-dimensional PCA with matching score level fusion for face recognition. Neural Computing & Applications, 2013, 23(1): 169-174（SCI）
[57] Yong Xu, Zizhu Fan, Qi Zhu. Feature space-based human face image representation and recognition. Optical Engineering, 2012, 51(1): 017205（SCI）
[58] Yong Xu, Qi Zhu, David Zhang. Combine crossing matching scores with conventional matching scores for bimodal biometrics and face and palmprint recognition experiments. Neurocomputing, 2011, 74(18): 3946-3952（SCI）
[59] Qi Zhu. Reformative nonlinear feature extraction using kernel MSE. Neurocomputing, 2010, 73(16): 3334-333 (SCI)
[60] Yong Xu, Qi Zhu. Protein secondary structure prediction via kernel minimum squared error. international conference on advanced computer control, 2011: 34--38 （EI）
[61] Rui Zhang, Xiangyu Xu, Qi Zhu. Semantic-Guided High-Order Region Attention Embedding for Zero-Shot Learning. 2021 13th International Conference on Advanced Computational Intelligence (ICACI), 2021: 266--272 (EI)
[62] Jing Yang, Qi Zhu*, Rui Zhang, Jiashuang Huang, Daoqiang Zhang. Unified Brain Network with Functional and Structural Data. MICCAI 2020 （EI）
[63] Huijie Li, Qi Zhu, Rui Zhang, Daoqiang Zhang. Multi-modality Low-Rank Learning Fused First-Order and Second-Order Information for Computer-Aided Diagnosis of Schizophrenia. international conference on intelligent science and big data engineering, 2019: 356--368 （EI）
[64] Xu Xiangyu, Xu Nuoya, Li Huijie, Zhu Qi*. Multi-spectral Palmprint Recognition with Deep Multi-view Representation Learning. International Conference on Machine Learning and Intelligent Communications, 2019: 748--758 （EI）
[65] Tao Zhang, Zhongnian Li, Qi Zhu, Daoqiang Zhang. Improved Procedures for Training Primal Wasserstein GANs. 2019 IEEE SmartWorld, 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00286 （EI）
[66] Hongqiang Wei, Qi Zhu, Donghai Guan, Weiwei Yuan, Asad Masood Khattak, Francis Chow. Improved label noise identification by exploiting unlabeled data. 2017 International Conference on Security, Pattern Analysis,and Cybernetics (SPAC) （EI）
[67] Ning Yuan, Donghai Guan, Qi Zhu, Weiwei Yuan. Self-paced learning for multi-modal fusion for alzheimer's disease diagnosis. 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2017 （EI）
[68] Qi Zhu, Qingxiang Feng, Jiashuang Huang, Dan Zhang. Sparse representation classification based on difference subspace. congress on evolutionary computation, 2016: 4244--4249 （EI）
[69] Qingxiang Feng, Qi Zhu, Chun Yuan, Ivan Lee. Multi-linear regression coefficient classifier for recognition. congress on evolutionary computation, 2016: 1382--1387 （EI）
[70] Qi Zhu, Baisheng Dai, Zizhu Fan, Zheng Zhang. Fast Sparse Representation Classification Using Transfer Learning. International Conference on Cloud Computing, 2015: 501--509 （EI）
[71] Zizhu Fan, Ming Ni, Qi Zhu, Yuwu Lu. Kernel sparse representation based classification for undersampled problem. 2014 International Conference on Smart Computing, 10.1109/SMARTCOMP.2014.7043839 （EI）
[72] Yong Xu, Jian Yang, Jiajie Xu, Qi Zhu, Zizhu Fan. Design and Implementation of a Bimodal Face Recognition System. international conference on intelligent science and big data engineering, 2013: 457--464 （EI）
[73] Qi Zhu, Yong Xu, Jing Hua Wang, Zizhu Fan. Kernel based sparse representation for face recognition. International Conference on Pattern Recognition, （EI）
[74] Yong Xu, Qi Zhu. PCA-based multispectral band compression and multispectral palmprint recognition. 2011 International Conference on Hand-Based Biometrics, 10.1109/ICHB.2011.6094303 （EI）
[1] 朱旗,,等.Multi-spectral Palmprint Recognition with Deep Multi-view Representation Learning.International Conference on Machine Learning and Intelligent Communications,2019
[2] 朱旗,,等.Multi-modality Low-Rank Learning Fused First-Order and Second-Order Information for Computer-Aided Diagnosis of Schizophrenia.International Conference on Intelligent Science and Big Data Engineering,2019
[3] 朱旗,,等.Cross-spectral palmprint recognition with low-rank canonical correlation analysis.Multimedia Tools and Applications,2019
[4] 朱旗,,等.Cognitive driven multilayer self-paced learning with misclassified samples.Complexity,2019
[5] 朱旗,,等.An alternative to face image representation and classification.Intl. J. Mach. Learn. Cybern.,2019
[6] 朱旗,,等.Multi-modal AD classification via self-paced latent correlation analysis.Neurocomputing,2019
[7] 朱旗,,等.Hybrid Functional Brain Network With First-Order and Second-Order Information for Computer-Aided Diagnosis of Schizophrenia.FRONTIERS IN NEUROSCIENCE,2019
[8] 朱旗,,等.Self-paced Learning for Multi-modal Fusion for Alzheimer's Disease Diagnosis.2017 INTERNATIONAL CONFERENCE ON SECURITY, PATTERN ANALYSIS, AND CYBERNETICS (SPAC),2017
[9] 朱旗,,等.Non-negative discriminative brain functional connectivity for identifying schizophrenia on resting-state fMRI.BIOMEDICAL ENGINEERING ONLINE,2018
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