近五年发表学术论文10余篇，其中SCI论文12篇，授权发明专利1项。 学术论文： [12] Lili Zhang*, Baozhi Cheng. A Combined Model based on Stacked Autoencoders and Fractional Fourier Entropy for Hyperspectral Anomaly Detection [J]. International Journal of Remote Sensing, 2021, 42(10):3611–3632. (SCI) [11] Lili Zhang*, Baozhi Cheng. Transferred CNN Based on Tensor for Hyperspectral Anomaly Detection [J]. IEEE geoscience and remote sensing letters, 2020, 17(12):2115-2119. (SCI) [10] Lili Zhang, Baozhi Cheng*. Sparse representation and modified tensor projection for hyperspectral anomaly detection [J].Infrared Physics & Technology, 2020,106: 103256. (SCI) [9] Lili Zhang*, Baozhi Cheng. A stacked autoencoders-based adaptive subspace model for hyperspectral anomaly detection [J]. Infrared Physics & Technology, 2019, 96:52-60. (SCI) [8] Lili Zhang*, Baozhi Cheng. A joint tensor-based model for hyperspectral anomaly detection [J]. Geocarto International, 2019(12):1-13. (SCI) [7]Lili Zhang*, Baozhi Cheng and Yuwei Deng.A tensor-based adaptive subspace detector for hyperspectral anomaly detection [J].International Journal of Remote Sensing, 2018, 39(8):2366–2382. (SCI) [6] Chunhui Zhao, Lili Zhang*. Spectral-spatial stacked autoencoders based on low-rank and sparse matrix decomposition for hyperspectral anomaly detection [J]. Infrared Physics & Technology, 2018, 92:166-176. (SCI) [5] Chunhui Zhao, Lili Zhang*, Baozhi Cheng. A local Mahalanobis-distance method based on tensor decomposition for hyperspectral anomaly detection [J]. Geocarto International, 2017:1-37. (SCI) [4]Lili Zhang, Chunhui Zhao*. Tensor decomposition-based sparsity divergence index for hyperspectral anomaly detection [J]. J Opt Soc Am A Opt Image Sci Vis, 2017, 34(9):1585-1594. (SCI) [3]Lili Zhang, Chunhui Zhao*. Hyperspectral anomaly detection based on spectral–spatial background joint sparse representation [J]. European Journal of Remote Sensing, 2017, 50(1):362-376.(SCI) [2] Lili Zhang, Chunhui Zhao*. A spectral-spatial method based on low-rank and sparse matrix decomposition for hyperspectral anomaly detection [J]. International Journal of Remote Sensing, 2017, 38(14):4047-4068. (SCI) [1] Lili Zhang, Chunhui Zhao*. Sparsity divergence index based on locally linear embedding for hyperspectral anomaly detection [J]. Journal of Applied Remote Sensing, 2016, 10(2):025026.(SCI) 发明专利： [1] 赵春晖，张丽丽，成宝芝，闫奕名，崔颖.基于空谱联合背景共同稀疏表示的高光谱异常检测方法，ZL 2016 1 0363080.6，授权公告日：2018年10月26日. | 
