计算机视觉

人工智能

大数据分析

一、论文

[66] Liang, L.; Gao, Z. SharDif: Sharing and Differential Learning for Image Fusion. Entropy 2024, 26, 57. https://doi.org/10.3390/e26010057

[65] Liang L, Shen X, Gao Z. IFICI: Infrared and visible image fusion based on interactive compensation illumination[J]. Infrared Physics & Technology, 2023: 105078.

[64] Zheng Y, Gao Z*, Zuo C. Complementary double pulse-width-modulation for 3D shape measurement of complex surfaces[J]. Optics & Laser Technology, 2023, 167: 109765. SCI 检索

[63] Zhang Z, Ding C, Gao Z*, et al. ANLPT: Self-Adaptive and Non-Local Patch-Tensor Model for Infrared Small Target Detection[J]. Remote Sensing, 2023, 15(4): 1021. SCI 检索

[62] Long j, Xie C, Gao Z*  High discriminant features for writer-independent online signature verification, Mulitimedia Tools and Application, 2023,  SCI

[61] Shu J, Xie C*, Gao Z. Blind Restoration of Atmospheric Turbulence-Degraded Images Based on Curriculum Learning[J]. Remote Sensing, 2022, 14(19): 4797.  SCI

[60] Jian P, Gao Z*, Multi-frame Blind Restoration of Space Target Images with Image Quality Prior[J]，Applied Soft Computing, 2022，SCI.

[59] Cheng P, Gao Z*, Zhou B, Zuo C, Optimization and regularization of complex task decomposition for blind removal of multi-factor degradation[J], Visual Communication and Image Representation, 2022. SCI.

[58] Zhou S, Gao Z*, Xie C. Dim and small target detection based on their living environment[J]. Digital Signal Processing, 2021: 103271. SCI: WOS:000710170600001

[57] Gao, Z. , Q. Wang , and C. Zuo . A total variation global optimization framework and its application on infrared and visible image fusion. Signal Image and Video Processing 20(2021). SCI: WOS:000673882100002

[56] Peijian Zhu,Chunzhi Xie,Zhisheng Gao*,Multi-Frame Blind Restoration for Image of Space Target With FRC and Branch-Attention,IEEE Acess, 2020,SCI检索(WOS:000579349200001)

[55] Gongping Cheng,Zhisheng Gao*,Learning a Multi-scale Deep Residual Network of Dilated-Convolution for Image Denoisin,IEEE 5th International Conference on Cloud Computing and Big Data Analytics,2020,EI检索(20202308788776).

[54] Qingqing Luo, Zhisheng Gao*, Chunzhi Xie,Improved GM-PHD filter based on threshold separation clusterer for space-based starry-sky background weak point target tracking,Digital Signal Processing, Volume 103, 2020, 102766, ISSN 1051-2004, https://doi.org/10.1016/j.dsp.2020.102766.SCI检索(WOS:000539114000005)

[53] Chen G, Gao Z*, Wang Q, et al. Blind de-convolution of images degraded by atmospheric turbulence[J]. Applied Soft Computing, 2020: 106131.SCI检索(WOS:000520042200020)

[52] Li Z, Li Y, Gao Z*. Spatiotemporal representation learning for video anomaly detection[J]. IEEE Access, 2020.SCI检索(WOS:000524658400003)

[51] Luo Q, Gao Z*, Xie C. Combined penalized weights based GM-PHD for point target tracking in starry-sky background[J]. Optik, 2020: 164145.SCI检索(WOS:000520025500040)

[50] Wang Q, Gao Z*, Xie C, et al. Fractional-order total variation for improving image fusion based on saliency map[J]. Signal, Image and Video Processing, 2020: 1-9. SCI:WOS:000507364700001

[48] Zhang C, Feng Z, Gao Z, et al. Salient feature multimodal image fusion with a joint sparse model and multiscale dictionary learning[J]. Optical Engineering, 2019, 59(5): 051402.

[48] Chen G, Gao Z*, Wang Q, et al. U-net like deep autoencoders for deblurring atmospheric turbulence[J]. Journal of Electronic Imaging, 2019, 28(5): 053024.SCI:WOS:000494983500024

[47] Zhisheng Gao, Jiao Dai, Chunzhi Xie, Dim and small target detection based on feature mapping neural networks, Journal of Visual Communication and Image Representation,Volume 62, 2019, Pages 206-216, ISSN 1047-3203, https://doi.org/10.1016/j.jvcir.2019.05.013.SCI:WOS:000476962600019

[46]Chengfang Zhang, Liangzhong Yi, Ziliang Feng, Zhisheng Gao, Xin Jin, Dan Yan，Multimodal image fusion with adaptive joint sparsity model，Multimodal image fusion with adaptive joint sparsity model, Journal of Electronic Imaging 28(1), 013043 (21 February 2019). https://doi.org/10.1117/1.JEI.28.1.013043  ,SCI:IDS 号:HN3XY

[45] 梁诚，蒲方圆，梁磊，高志升，结合灰度信息的压敏漆图像配准，光电工程，2019，02期。CSCD:6448264

[44] Gao Z, Shen C, Xie C. Stacked convolutional auto-encoders for single space target image blind deconvolution[J]. Neurocomputing, 2018. SCI ：GS0CG

[43] Gao, Zhisheng,Yang,Miao,Xie,Chunzhi,Space target image fusion method based on image clarity criterion,Optical Engineering, v 56, n 5, May 1, 2017,  SCI EX2YZ

[42] Gao, ZS (Gao, Zhisheng); Li, YS (Li, Yaoshun); Xie, CZ (Xie, Chunzhi),Parameter Estimation for the Field Strength of Radio Environment Maps,WIRELESS COMMUNICATIONS & MOBILE COMPUTING,  SCI:FO0DK,

[41] 高志升，沈沉，李瑶顺，基于P系统的湍流模糊图像盲复原，光学精密工程，2017，10z（25）：304-311，ei:20180504689540

[40] 杨淼，沈沉，高志升，基于F-B模板的遥感图像港口高精度分割提取，光学精密工程，2017，10z（25）：205-214,ei:20180504689527

[39] Zhisheng Gao, Chengfang Zhang, Texture clear muti-modal image fusion with joint sparsity model, optic, 2016,130:255-265, sci：EH4XO

[38] 高志升，耿龙，张铖方，胡占强，采用目标背景建模的毫米波弱小目标检测，光学精密工程，2016，10（24）:2601-2611.ei:20164603006193

[37] Gao Zhilv, Yue Zhen, Gao Zhisheng, Pei, Zheng, Combining NSCT and high discrimination features for eye location, ICIC Express Letters,10(11): 2685-2694,2016;

[36] 高志升, 张铖方, 胡占强, 等. 基于差分进化 P 系统的多模态图像配准[J]. 光学精密工程, 2015, 23(10z): 684-694.

[35] J Li，Z Gao，Z Pei The radio environment map parameter estimation using kriging method based on propagation model. Journal of Computational Information Systems. 2015,11(20):7607-7616

[34] Li M, Gao Z, Pei Z, et al. Fuzzy Markov Model Based on FCM for Electromagnetic Environment Parameters Prediction[J] . JOURNAL OF INFORMATION &COMPUTATIONAL SCIENCE, 2015, 12(5): 1713-1722.

[33] Zhen Yue, Zhisheng Gao, Zhanqiang Hu and Zheng Pei.Image Denoising Algorithm Based on the Dyadic Wavelet-NSCT Transform and Discriminant Thresholding. ICIC Express Letters. 2015,9(4)1167-1172.

[32] Zhen Yue, Zhisheng Gao, Zhanqiang Hu and Zheng Pei. Combining retinex theory and high discrimination features for eye location. ICIC Express Letters. 2015, 6(9) 2385-2393.

[31] 高志升, 岳桢, 张铖方, 等. 基于小波光照归一化和高判别力特征的人眼定位算法[J]. 西华大学学报 (自然科学版), 2015 (2015 年 03): 1-5, 12.

[30] Zhisheng Gao,Zhanqiang Hu, Zhen Yue, and Zheng Pei. High generalization features design and selection for face detection. Journal of Computational Information Systems.2014.10(19) 8805-8812.

[29] Li M, Yi L, Gao Z, et al. Support Vector Machine (SVM) based on membrane computing optimization and the application for C-band radio abnormal signal identification[J]. JOURNAL OF INFORMATION &COMPUTATIONAL SCIENCE, 2014, 11(11): 3683-3693.

[28] Gao Z, Shi P, Karimi H R, et al. A mutual GrabCut method to solve co-segmentation[J]. EURASIP Journal on Image and Video Processing, 2013, 2013(1): 20. sci:150YW

[27] 高志升, 袁红照, 杨军. 基于旋转不变局部相位量化特征的人脸确认算法研究倡[J]. 计算机应用研究, 2012, 29(1).

[26] 高志升, 谢春芝. 系统化方法在 JAVA EE 教学中的运用[J]. 电脑知识与技术, 2012, 30: 037.

[25] 高志升, 谢春芝. 具有高斯噪声不变性的特征描述算子[J]. Computer Engineering and Applications, 2011, 47(31).

[24] Gao Z S, Xie C Z. PI Diagram Based Face Detection with AdaBoost in Color Image[C]//Artificial Intelligence and Computational Intelligence, 2009. AICI'09. International Conference on. IEEE, 2009, 2: 432-435.

[23] 高志升.改造敏捷模型在高校软件开发中的实践[J]. 电脑知识与技术: 学术交流, 2010, 6(3): 1772-1773.

[22] 高志升. 软件测试技术教学方法[J]. 电脑知识与技术, 2010, 3(6): 9.

[21] 高志升. 袁红照, 杨军. 融合CDI 和 LBP 的人脸特征提取与识别算法[J]. 光电子. 激光, 2010, 21(1): 112-115.

[20]Gao Z S, Xie C Z. Notice of Retraction The Study of Content Simulation Using in the Software Project Management Teaching[C]//Education Technology and Computer Science (ETCS), 2010 Second International Workshop on. IEEE, 2010, 3: 576-578.

[19] Gao Z S, Yuan H Z. Face Recognition Based on SFLBP[C]//Education Technology and Computer Science (ETCS), 2010 Second International Workshop on. IEEE, 2010, 2: 202-205.

[18] 高志升.彩色图像人脸检测新方法 [C][C]//第十四届全国图象图形学学术会议论文集. 2008.

[17] 高志升. 基于多 agent 的语义 web 服务自动组合方法的研究 [J][D]. 西华大学, 2006.

[16] 高志升, 刘兴伟. 基于语义 P2P 的 Web 服务模型[J]. 阿坝师范高等专科学校学报, 2005, 22(3): 59-61.

[15] 高志升, 刘兴伟. 基于工作流的电信业务开通系统建模与控制[J]. 西华大学学报: 自然科学版, 2005, 24(5): 4-6.

[14] Gao Z S. Automatic defogging method for image based on the physical model, Yi Qi Yi Biao Xue Bao, 2008-08-01.

[13] Gao Z S, Zhang X Q, Yuan H Z. A New Method for Detecting and Removing the Specularities in Color Facial Images[C]//Natural Computation, 2008. ICNC'08. Fourth International Conference on. IEEE, 2008, 4: 43-47.

[12] Gao Z S, Xie C Z. PI Diagram Based Face Detection with AdaBoost in Color Image[C]//Artificial Intelligence and Computational Intelligence, 2009. AICI'09. International Conference on. IEEE, 2009, 2: 432-435.

[11] 张秀琼, 高志升, 袁红照. 基于物理模型的自动化图像去雾方法[C]//第六届全国信息获取与处理学术会议论文集 (1). 2008.

[10] XIE C, DU Y, GAO Z. Algorithm for Construction of Evolution-Based Concept Lattices with Application to Public Sentiment Prediction[J]. Journal of Information and Computational Science, 2011, 8(16): 4201-4208.

[9] 唐剑梅, 高志升. 软件工程在“软件开发设计实训”课程中的应用[J]. 电脑知识与技术: 学术交流, 2013, 8(11): 7526-7528.

[8 Ruan Y, Pei Z, Gao Z. Linguistic interval 2-tuple power aggregation operators and their applications[J]. International Journal of Computational Intelligence Systems, 2013, 6(2): 381-395.

[7] Chunzhi XIE，Yajun DU, Zhisheng GAO Restricted Boltzmann Machines with SVM for Object Recognition， Journal of Computational Information Systems， 2014.11.1， 10（21）：9199~9206

[6] Fei Zhao, Zhisheng Gao, Jian Li, Zheng Pei. Automatic Spectrum Occupancy Measurement Methods based on historgram featrues, Journal of Computational Information Systems,2014,10(10): 4411-4418.

[5] Li M, Yi L, Pei Z, Gao Zhisheng. Chaos time series prediction based on membrane optimization algorithms[J]. The Scientific World Journal, 2015, 2015.

[4] Peng H, Luo X, Gao Z, et al. A novel clustering algorithm inspired by membrane computing[J]. The Scientific World Journal, 2015, 2015.

[3] 李忠凯, 贾年, 高志升. 基于面向服务的无线电监测考试保障系统的设计[J]. 成都工业学院学报, 2016, 19(2): 38-41.

[2] 杨军, 高志升, 袁红照, 等. 基于 LBP 特征和贝叶斯模型的单样本人脸识别[J]. 光电子. 激光, 2011, 22(5): 763-765.

[1] 杨军, 张秀琼, 高志升, 袁红照. (2010). 用于人脸识别的两类主成分分析融合. 计算机工程与应用, (1), 194-195.

二、专利

[9] 一种基于复杂任务分解正则化的图像去模糊模型、方法及设备

[8] 全变分深度学习优化的红外可见光图像融合方法

[7] 基于阈值分离聚类器的天基星空背景弱小点目标跟踪方法

[6] 一种特征映射神经网络的弱小目标检测方法

[5] 基于卷积自编吗卷积神经网络的空间目标图像复原方法 

[4] 无线电监测态势预测系统

[3] 一种基于区域相似样例学习的稀疏去噪方法 

[2] 基于联合稀疏模型的边缘清晰图像融合方法

[1] 基于局部相似样例学习的稀疏去噪方法

三、项目

24. 企事业委托，船舶舱室涂层图像检测技术研制技术服务项目，2023.8.15-2024.01

23. 企事业委托，跳伞训练视频分析系统研制，2023.6.30-2023.12.30

22. 四川省科技厅重点研发项目，动态环境弱小目标视频图像智能处理，2023.01-2024.12

21. 企业委托，智慧养殖AI服务平台，2022.09-2023.06

20. 企业委托，模型试验三维形变测量系统，2022.07-2023.05

19. 企业委托，基于面结构光的三维测量系统及配套，2022.05-09

18. 四川省科技厅重点研发项目，基于CNG、LNG特种设备的智能监管大数据平台及应用，2021.01-2023.12

17.企业委托，影像数据库管理软件，2020.09-2021.05

16.企业委托，频谱占用的多域图形化表示方法研究和软件开发，2019.12-2021.12

15.企业委托，mop，2018.12-2019.05

14.企业委托，xxx业务信息系统，2018.07-2019.12

13.西华大学校重点，基于目标样例的自适应光学图像重建技术，2017.12-2020.12.

12.教育部“春晖计划”合作科研项目，基于目标样例的自适应光学图像重建技术，2016/12-2018/12

11.26基地项目，PSP图像处理关键技术研究，2016/10-2018/12

10.企业委托项目，无线电监测站自动巡检系统，2015/12-2017/08

9.企业委托项目，重载铁路新型无线电宽带通信系统频谱规划研究，2016/12-2017/06

8.无线电监测通信协议(RMTP)验证测试系列软件开发,2015/01-2017/12

7.宇航动力学国家重点实验室课题，xxxxxx、基于特征识别的多光谱空间目标图像融合方法研究，2015/01-2016/12

6.国家973计划专题，xxxxxx、毫米波辐射xxxx目标检测、2014/05-2017/12

5.企业委托，智能路灯云平台，2017.09-2018.06

4.企业委托，辅警考勤系统，2017.05-2017.09

3.预研重点基金，基于航天xxx机理研究，2013-2016.12 

2.企业委托，水上无线电监测系统，2015.08-2015.10

1.四川省无线电监测站，无线电知识学习与考评系统，2012.01-2013.05

智能数据分析

数据挖掘

计算机视觉

计算机网络

[1] 四川省科学技术进步二等奖