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学术论文


在核心期刊及国际会议上发表论文250余篇,其中被SCI、EI检索近180余篇。

近期合作发表的部分国外期刊论文如下:

 

1.       Li Ming, Wu Yan, et al. SAR Image Segmentation Based on Mixture Context and Wavelet Hidden-Class- Label Markov Random Field. 

       Computers and Mathematics with Applications.2009, 57(6): 961-969.

2.    Zhang Peng,Li Ming , et al. Unsupervised Multi-class Segmentation of SAR images  using Fuzzy Triplet Markov Fields Model. 

       Pattern Recognition. 2012, 45(11): 4018-4033. 

3.    Wu Yan, Li Ming , Zhang Peng, et al. Unsupervised multi-class segmentation of SAR images using triplet Markov fields models based on edge penalty. 

       Pattern Recognition Letters. 2011, 3211: 1532-1540.

4.    Zhang Peng, Li Ming, et al.  An Improved Particle Filter Algorithm Based on Markov Random Field Modeling in Stationary Wavelet Domain for SAR Image Despeckling. 

       Pattern Recognition Letters2012, 33(10): 1316–1325.

5.    Zuo Lei, Li Ming, et al. An Efficient Method for Detecting Slow-moving Weak Targets in Sea Clutter Based on Time-frequency Iteration Decommended.

       IEEE Trans. on Geoscience and Remote Sensing 2013, 51(6): 3659–3672. 

6.   Zhang Peng, Li Ming, et al.  SAR image multiclass segmentation using a multiscale TMF model in Wavelet Domain. 

       IEEE Geoscience and Remote Sensing Letters vol.9,no.6, pp1099-1103, 2012.

7.    Wu Yan,Zhang Peng, Li Ming, et al.   SAR Image Multiclass Segmentation Using a Multiscale and Multidirection TMF Model in NSCT Domain. 

       Imformation Fusionvol 14, pp. 441-449, 2013.

8.    Wan Fan,Wu Yan.., Li Ming,et al.   Unsupervised Change Detection on SAR Images Using Triplet Markov Fields Model. 

       IEEE Geoscience and Remote Sensing Lettersv 10, n 4, p 697-701, July 2013 

9.    Wu Yan, Li Ming , et al. Fusion Segmentation Algorithm for SAR Images Based on HMT in Contourlet Domain and D-S Theory of Evidence.

       Computational Science and Its Applications.Vol.5593,pp937-951,2009. 

10.   Zhang Peng, Li Ming , et al. Unsupervised SAR Image Segmentation Using a Hierarchical TMF Model.   

       IEEE Geoscience and Remote Sensing Letters. vol.10,no.4, pp971-975, 2013. 

11.   Zuo Lei,Li Ming,Zhang Xiao-wei.Two helicopter classification methods with a high PRF radar.

       IET Radar,  Sonar & Navigation ,vol. 7, no. 3, pp. 312–320, 2013.

12    Wan Fan,Wu Yan..,Li Ming,et al.  ,,.Unsupervised SAR Image Segmentation Using Higher Order Neighborhood Based Triplet Markov Fields Model.

       IEEE Trans on Geoscience and Remote Sensing, Vol.52, No.8, pp.5193–5205, August 2014. 

13.   Liu Gaofeng, Li Ming, Zhang Peng. Fast solution to nonnegative eigenvalue decomposition for polarimetric SAR.

       Electronics Letters, Vol.49No.6, pp419-420.2013.  

14.  Liu Gaofeng, Li Ming , et al. Four-Component Scattering Power Decomposition of Remainder Coherency Matrices Constrained for

       Nonnegative Eigenvalues ,

      IEEE Geoscience and Remote Sensing Letters. vol.11,no.2, pp494-498, 2014.  

15.  Zuo Lei, Li Ming, et al,CFAR Detection of Range-Spread Targets Based on the Time-Frequency Decomposition Feature of Two Adjacent Returned Signals.

       IEEE Transactions on Signal Processing.Vol.61,No.24, pp6307-6319.2013. 

16.   Chen Hongmeng, Li Ming, et al.Resolution enhancement for DBS imaging .  

      IET Radar, Sonar & Navigation.Vol 9, No 7, pp 843-851, August , 2015 .

17.   Fan Yifei,Luo Feng, Li Ming, et al.The Fractal Properties of AR Spectrum and its application on Weak Target Detection in Sea Clutter    

       Background .  IET Radar, Sonar & Navigation.Vol 9, No 7, pp 835-842 , August 1, 2015.

18. Liu Gaofeng, Li Ming , et al. PolSAR Image Classification Based on Wishart TMF with Specific Auxiliary Field .

      IEEE Geoscience and  Remote Sensing Letters, vol.11,no.7, pp1230-1234, 2014 

19.  Li Hejing,Li Ming,Zhang Peng. Semi-supervised SAR Image Change Detection Based on Hybrid Discriminative Random Fields .

      IEEE Geoscience and Remote Sensing Letters, Vol.12, No.4, pp.910–914, April, 2015 .   

20.   Zuo Lei, Li Ming, et al.Range-spread target detector using the frequency rate function. 

        IET Radar, Sonar & Navigation.vol 8, no 7, p 749-756, 2014 

21.  Zhang Xiaowei,Li ming,et al. Adaptive Subspace Detection for Wideband Radar Using Sparsity in Sinc Basis.

       IEEE Geoscience and Remote Sensing  Letters,vol.11,no.11, pp1916-1920, 2014 . 

22.   Jia Lu, Li Ming, et al. Semi-supervised SAR Image Change Detection Using a Cluster-Neighborhood Kernel ,

         IEEE Geoscience and Remote Sensing Letters, vol.11,no.8, pp1443-1447, 2014 . 

23.   Zhang XiaoweiLi minget al.   Compressed Sensing Detector for Wideband Radar Using the Dominant Scatterer.

        IEEE Signal Processing Letters. vol.21,no.10, pp1275-1279, 2014 . 

 24.      Jia Lu,Li Ming,et al . SAR Image Change Detection Based on Iterative Label-Information Composite Kernel Supervised by    Anisotropic Texture.

        IEEE Trans. on Geoscience and Remote Sensing.  Vol.53, No.7, pp.3960–3973, July, 2015 

25.  Cheng Hongmeng,Li Ming, Zhang Peng Super-resolution DBS Imaging via Sparse Representation

       IET Radar, Sonar & Navigation. v 10, n 3, p 442-448, March 1, 2016  .

26.  An Lin,Li Ming,Discriminative Random Fields Based on Maximum Entropy Principle for Semi-supervised SAR Image Change Detection.

      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(J-STARS).  Vol9,No8 , pp3395-3404,August,2016.

27.   Cheng Hongmeng,Li Ming.Sparse super-resolution imaging for airborne single channel forward-looking radar in expanded beam space via lp regularization.

        Electronics Letters Vol 51, No11, May 28, 2015 ,p 863-865 .

28.      An Lin,Li Ming. Multicontextual Mutual Information Data for SAR Image Change Detection.

       IEEE Geoscience and Remote Sensing Letters,Vol.12, No.9, pp.1863–1867, Sept, 2015。 

29.  Song Wanying,Li Ming, Zhang Peng. The WG Distribution for Multi-Look Polarimetric SAR Data and Its Application.

       IEEE Geoscience and Remote Sensing Letters,Vol.12, No.10, pp.2056–2060, Oct, 2015。 

30.   Zhang Peng , Li Ming, Wu Yan ,Li Hejing. Hierarchical Conditional Random Fields Model for Semisupervised SAR Image Segmentation.

       IEEE Trans on Geoscience and Remote Sensing,Vol 53, No 9, pp 4933-4951, September , 2015 .

31. Jia Lu,Li Ming. Unsupervised Remote Sensing Image Change Detection with Fusion of Multiple Wavelet Kernels.

       IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(J-STARS). Vol9,No8,pp3405-3418, 2016。

32.  Zuo Lei,Li Ming,Liu Zheng. Range-spread target detection using time delay-frequency matched filter.

       IET Radar, Sonar & Navigation.   v 10, n 4, pp742-748, April 1, 2016 

33.  Zhang Peng ,Li Ming ,Unsupervised SAR image segmentation using high-order conditional random fields model based on product-of-experts。

       Pattern Recognition Letters,v 78,pp 48-55,July 15, 2016   

34.    Wang  Zeyu ,Li Ming . Persymmetric Detectors of Distributed Targets in Partially Homogeneous Disturbance,

        Signal Processing, Vol 128,Pp382-388,2016。

35 .   Jia Lu,Li Ming. SAR Image Change Detection Based on Correlation Kernel and Multistage Extreme Learning Machine.

       IEEE Trans on Geoscience and Remote Sensing. Vol54,No10,pp5993-6006, 2016  .

36.   Fan Yifei,Luo Feng,Li Ming. Weak Target Detection in Sea Clutter Background Using Local-Multifractal Spectrum with Adaptive Window Length 。

        IET Radar,Sonar & Navigation. Vol 9, No 7, pp 835-842 , August 1, 2015.

37.   Zuo Lei,Li Ming,Liu Zheng.Range-spread target detection based on the matched ambiguity function。

       IET Radar, Sonar & Navigation.  Vol10,No7,pp1213-1219 .2016。 

38.   Chen Hongmeng ,Li Ming.  Synthetic Bandwidth Azimuth Modulation Imaging Radar for Airborne single-channel Forward-looking  Imaging.

        Signal Processing, Vol 130,Pp86-92.2017。

39.   Zuo Lei,Li Ming, A High Resolution Time-Frequency Rate Representation and the Cross Term Suppression.

        IEEE Trans. on Signal Processing.  v 64, n 10,pp 2463-2474,  May 15,2016。 

40.   Zeyu Wang, Ming Li .Time-dimension Reduced Track-Before-Detect Algorithm for Slow-moving Weak   Multi-Targets in Heavy Clutter Environment

       IET Signal Processing,  v 11, n 4, p422-428 , Jun, 2017。 

41. Hongmeng Chen,Ming Li .Cross-range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture Extrapolated Sparse  Representation . 

      IEEE Geoscience and Remote Sensing Letters, Vol.14, No.9,  September , 2017. 

42   Song Wanying,Li Ming, Zhang Peng .Unsupervised PolSAR Image Classification and Segmentation using Dirichlet Process Mixture Model and 

       Markov Random Fields with Similarity Measure。

      IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(J-STARS). v 10, n8, p3556-3568 , Aug, 2017.

43  Runqing Cao, Ming Li .A New Method for Parameter Estimation of High-order Polynomial-phase Signals .  

      Signal Processing, Vol 142January2017.

44.  Lei Zuo, Ming Li,xianggen Xia. New Smoothed Time-Frequency Rate Representations for Suppressing Cross Terms .

      IEEE Transactions on Signal Processing. v 65, n 3,pp 733-747,February 1, 2017  

45    Zeyu Wang, Ming Li. Model-based Rao test for adaptive range-spread target detection。

      Digital Signal Processing,Vol 69October 2017.

46.             Zeyu Wang, Ming Li. Adaptive Detection of a Subspace Signal in Signal-Dependent Interference。

      IEEE Transactions on Signal Processing. v 65, n 18,pp 4812-4820,September 15, 2017