Qinghua Zhao

Qinghua Zhao

Assistant Professor,College of Information Engineering,NUFE

Journal Papers

[20] Sang, X., Lu, H., Q. Zhao, Zhang, F. and Lu, J., Nonconvex regularizer and latent pattern based robust regression for face recognition. Information Sciences, 547, pp.384-403, 2020. (SCI，1区，IF=5.91)

[19] Lu, H., Shen, Z., Sang, X., Q. Zhao, & Lu, J. Community detection method using improved density peak clustering and nonnegative matrix factorization. Neurocomputing, 415, 247-257, 2020. (SCI，2区，IF=4.072)

[18] Sang, X., Xu, Y., Lu, H., Q. Zhao, Ali, Z., & Lu, J. Robust mixed-norm constrained regression with application to face recognitions. Neural Computing & Applications, 2020. (SCI，2区，IF=4.664)

[17] Lu, H., Sang, X., Q. Zhao, & Lu, J. Community detection algorithm based on nonnegative matrix factorization and pairwise constraints. Physica A: Statistical Mechanics and its Applications, 545, 123491, 2020. (SCI，3区，IF=2.500)

[16] Lu, H., Q. Zhao, Sang, X., & Lu, J. Community Detection in Complex Networks Using Nonnegative Matrix Factorization and Density-Based Clustering Algorithm. Neural Processing Letters, 1-18. 2020.(SCI，3区，IF=2.591)

[15] Lu, H., Sang, X., Q. Zhao., & Lu, J. Community Detection Algorithm Based on Nonnegative Matrix Factorization and Improved Density Peak Clustering. IEEE Access, 8, 5749-5759. 2020. (SCI，2区，IF=4.098)

[14] Swati, Z. N. K., Q. Zhao, Kabir, M., Ali, F., Ali, Z., Ahmed, S., & Lu, J. Content-based brain tumor retrieval for MR images using transfer learning. IEEE Access, 7, 17809-17822, 2019. (SCI，2区，IF=4.098)

[13] Swati, Z. N. K., Q. Zhao, Kabir, M., Ali, F., Ali, Z., Ahmed, S., & Lu, J. . Brain tumor classification for MR images using transfer learning and fine-tuning. Computerized Medical Imaging and Graphics, 75, 34-46. 2019 (SCI，3区，IF=3.298)

[12] Q. Zhao., Swati, Z. N., Metmer, H., Sang, X., & Lu, J. Investigating executive control network and default mode network dysfunction in major depressive disorder. Neuroscience letters, 701, 154-161. 2019. (SCI，4区，IF=2.173)

[11] Q. Zhao., Sang, X., Metmer, H., Lu, J., & Alzheimer’s Disease NeuroImaging Initiative. Functional segregation of executive control network and frontoparietal network in Alzheimer’s disease. Cortex, 120, 36-48. 2019. (SCI，1区，IF=4.907)

[10] Q. Zhao., Ali, Z., Lu, J., & Metmer, H. . Structure Feature Learning: Constructing Functional Connectivity Network for Alzheimer’s Disease Identification and Analysis. In Chinese Conference on Biometric Recognition pp. 107-115. 2019, October.(CCBR 2019, Oral, 接收率16%).

[9] Sang, X., Q. Zhao, Lu, H., & Lu, J. . Weighted fuzzy time series forecasting based on improved fuzzy C-means clustering algorithm. In 2018 IEEE International Conference on Progress in Informatics and Computing (pp. 80-84). IEEE. 2018, December. (PIC, 2018).

[8] Q. Zhao, Xi Jiang, Shijie Zhao, Xintao Hu, Junwei Han, Jianfeng Lu.”Identifying Consistent Functional Brain Landmarks via Group-wise Sparse Representation of Concatenated Multitask fMRI Data”,IEEE 15th International Symposium on Biomedical Imaging (ISBI, 2018).

[7] Q. Zhao, Sang, X., & Lu, J. . Weighted group sparse functional connectivity modeling for Alzheimer’s disease identification. In 2018 IEEE 15th International Symposium on Biomedical Imaging pp. 541-544. IEEE. 2018, (ISBI, 2018).

[6] Q. Zhao, WXY Li, X Jiang, J Lv, J Lu, T Liu.”Functional brain networks reconstruction using group sparsity-regularized learning”.Brain Imaging and Behavior ,12,758-770. 2018. (SCI，2区，IF=3.985)

[5] Q. Zhao., Lu, H., Metmer, H., Li, W. X., & Lu, J. . Evaluating functional connectivity of executive control network and frontoparietal network in Alzheimer’s disease. Brain research, 1678, 262-272. 2018 (SCI，3区，IF=3.929)

[4] Metmer, H., Ji, C., Xiao, J., Q. Zhao.,& Lu, J. Evaluation of Default Mode Network In Mild Cognitive Impairment and Alzheimer’s Disease Individuals. International Journal of Biometrics and Bioinformatics, 11(1), 1. 2017

[3] Q. Zhao, J. Lu., J. Lv, X.Jiang, S.Zhao, T.Liu. “Exploring Brain Networks via Structured Sparse Representation of fMRI Data.” . In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 55-62. 2016.(MICCAI 2016, Top Conference).

[2] X Jiang, T Zhang, Q. Zhao, J Lu, L Guo, T Liu. “Fiber connection pattern-guided structured sparse representation of whole-brain fMRI signals for functional network inference.” (2015). In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 133-141.(MICCAI 2015, Top Conference).

[1] B Ge, M Makkie, J Wang, S Zhao, X Jiang, X Li，Q. Zhao, L Guo, T Liu.（.”Signal sampling for efficient sparse representation of resting state fMRI data”. pp. 1360-1363. 2015 (ISBI, 2015).