➢ 部分第一/通讯作者论文
[1] Xiaohui Yang, Li Tian, Yunmei Chen, et al. Inverse projection representation and category contribution rate for robust tumor classification, IEEE/ACM Transactions on Computational Biology and Bioinformatrics, 2020, 17(4): 1262-1275.
[2] Xiaohui Yang, Xiaoying Jiang, Chenxi Tian, et al. Inverse projection group sparse representation for tumor classification: a low-rank variation dictionary approach. Knowledge-Based Systems, 2020, 196: 105768.
[3] Xiaohui Yang, Wenming Wu, Yunmei Chen, et al. An integrated inverse space sparse representation framework for tumor classification. Pattern Recognition, 2019, 93: 293-311.
[4] Xiaohui Yang, Wenming Wu, Zhicheng Jiao, Lijun Yang. Deep unlabeled data-driven reinforcement learning model for tumor classification. Submitted to the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), 2019.
[5] Xiaohui Yang, Wenming Wu, Licheng Jiao. Deep unlabeled data-driven fusion model of representation learning and classification for robust tumor recognition. Submitted to IEEE Transactions on Image Processing, 2019.
[6] Xiaohui Yang, Wenming Wu, Xinxin, Limin Su, Liugen Xue. A deep generalized adaptive elastic net constraint-based NMF model and its applications in tumor recognition. Submitted to Pattern Recognition, 2019.
[7] Xiaohui Yang, Xiaoying Jiang, Chenxi Tian, Wenming Wu, Pei Wang. Inverse projection group sparse representation for tumor classification: a low-rank variation dictionary approach. Submitted to IEEE Transactions on Computational Biology and Bioinformatics. 2019.
[8] Xiaohui Yang, Huan Wu, Wenming Wu, Zheng Wang, Lijun Yang. Low rank and sparse pseudo-full space representation based classification model for robust face recognition. Submitted to Signal Processing: Image Communications. 2019（revision）
[9] Xiaohui Yang, Wenming Wu, Yunmei Chen, Xianqi Li, Juna Zhang, Dan Long, Lijun Yang. An integrated inverse space sparse representation framework for tumor classification. Pattern Recognition.2019, DOI: 10.1016/j.patcog.
[10] Wenming Wu, Xiaohui Yang (通信作者), Yunmei Chen, Juan Zhang, Dan Long, Lijun Yang, Chenxi Tian. Layer-wise pre-training low-rank NMF model for mammograms-based breast tumor classification. Journal of the Operations Research Society of China, 2019. (in press)（中国运筹学会会刊）
[11] 杨晓慧, 白欣宇, 乔江华, 陆寓非. 基于一种集成的信息基因选择方法的乳腺肿瘤识别研究. 中国肿瘤, 2019. (in press)
[12] Xiaohui Yang, Li Tian, Yunmei Chen, Lijun Yang, Shuang Xu, Wenming Wu. Inverse projection representation and category contribution rate for robust tumor classification, IEEE/ACM Transactions on Computational Biology and Bioinformatrics, 2018, DOI: 10.1109/TCBB.2018.2886334
[13] Xiaohui Yang, Fang Liu, Li Tian, Haifei Li, Xiaoying Jiang. Pseudo-full-space representation based classification for robust face recognition. Signal Processing: Image Communications. 2018, 60: 64-78.
[14] Xiaohui Yang, Chenxi Tian, Feiya Lv, Jing Zhang, Zhengjun Zha. Particle swarm programming-based interactive content-based image retrieval. The 2018 Pacific-Rim Conference on Multimedia (PCM 2018). September 21-22, Hefei, 2018, 11166, 99-111.
[15] 孙磊, 李禄全, 杨晓慧(通讯作者). 基于决策曲线分析的临床预后重要影响因素筛选. 中国卫生统计, 35(6): 846-849, 2018. (中国卫生信息学会会刊)
[16] Shuaijie Li, Xiaohui Yang (通讯作者). Novel image inpainting algorithm based on adaptive fourth-order partial differential equation. IET Image Processing, 2017, 11(10): 870-879.
[17] Xiaohui Yang, Feiya Lv, Lijun Cai Dengfeng Li. Adaptive learning region importance for region-based image retrieval. IET Computer Vision, 2015, 9(3):368-377.
[18] Xiaohui Yang, Lijun Cai. Adaptive region matching for region-based image retrieval by constructing region importance index. IET Computer Vision, 2014, 8(2): 141-151.
[19] XiaohuiYang, Licheng Jiao, Dengfeng Li. Directional filter for SAR image based on nonsubsampled Contourlet transform and immune clonal selection. International Journal of Automation and Computing. 2009, 6(3): 246-254.
[20] 杨晓慧, 李登峰. G-框架及其对偶框架的一些等式和不等式. 数学学报. 2009, 52(5):1033-1040.
[21] Xiaohui Yang, Licheng Jiao. Fusion algorithm for remote sensing images based on nonsubsampled Contourlet transform. Acta Automatica Sinica, 2008, 34(3): 41-45.
➢ 专著
[1] 杨晓慧，陈韵梅，周福娜，杨利军，刘芳著. 反投影稀疏表示模型及应用. 2018, 科学出版社. ISBN: 978-7-03-057629-3
[2] 李登峰,杨晓慧. 小波基础理论和应用实例. 2010, 高等教育出版社. ISBN: 978-7-04-029202-2
[3] 李登峰，杨晓慧，杨利军. 实变函数简明教程. 2009, 河南大学出版社. ISBN: 978-7-5649-0059-5.
➢ 主持或第一参加的科研项目
[1] 国家自然科学青年基金，60802061，18万，基于多尺度几何分析和SVM的Web图像检索技术研究，2009/01-2011/12，已结题，主持
[2] 国家自然科学面上基金，61071189， 36万，基于Bandelet变换的压缩域图像检索技术研究，2011/01-2013/.12，已结题，第2主持
[3] 国家自然科学面上基金，41771375， 63万，基于深度随机场的高空间分辨率遥感影像多语义分割，2018/01-2022/12，在研，参加
[4] 国家自然科学天元基金，11426087， 3万，信号时频分析与包络的数学模型，2015/01-2015/12，已结题，参加
[5] 河南省青年骨干教师项目，2013GGJS-027，4万，基于稀疏表示的个性化图像检索，2014/01-2016/12，已结题，主持
[6] 河南省自然科学基金，162300410061， 5万，融合脑电信号的图像识别和检索技术研究，2016/01-2018/12，已结题，主持
[7] 教育部重点实验室开放基金，IPIU012011004， 3万，图像检索中的相关反馈技术研究，2011/05-2013/05，已结题，主持
[8] 河南省教育厅科技攻关重点项目，14A120009，4万，基于稀疏表示的实时图像识别\检索关键技术研究，2014.1-2018.12，已结题，主持
[9] 河南大学新兴交叉及特色学科培育项目，xxjc20170003，10万，基于再生核的深度学习模型及其在乳腺癌早期识别中的应用，2017/09-2019/09, 在研，主持
[10] 河南大学第一届青年骨干教师项目，多尺度几何域统计模型的构建及其在图像处理中的应用研究，2013.1-2014.12，已结题，主持
➢ 国家发明专利
[1] 国家发明专利，第1，基于低秩变异字典和稀疏表示分类的人脸伪装检测及伪装类别检测方法，申请号：CN201810072104.1，公开号：CN108171215A
[2] 国家发明专利，第1，基于自适应学习区域重要性的交互式图像检索方法及系统，中国，2017. 2.8，ZL 201310749631.9
[3] 国家发明专利，第2，基于分层特征和遗传规划相关反馈的图像检索方法，中国，2018.7.17，ZL2013 1 0119320.4
➢ 国家软件著作权
[1] 第1，基于反投影稀疏表示学习的乳腺肿瘤实时识别系统V1.0，2018SR895646
[2] 第1，基于超声图像深层特征分析的宫颈癌前病变检测系统V1.0，2018SR921346
[3] 第1，基于深度随机森林的多人动态表情实时识别系统，2018SR855790
[4] 第1，基于联合熵的视频信息跳变检索系统，v1.0，2018SR762479
