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                                                                   I. 研究論文中的實現代碼

                        I.     Download matlab code of paper: DLWFDW_toolbox

                        Peng-Lang Shui, Image Denoising Algorithm via Doubly Local Wiener Filtering With Directional Windows in Wavelet Domain, IEEE Signal Processing Letter, vol.12(10), pp.681-684, October 2005.

                        II.    Download matlab code of paper: BWP toolbox

                        Peng-lang Shui, Zuo-feng Zhou, Jun-xia Li, Image Denoising Algorithm via Best Wavelet Packet Base using Wiener Cost Function, IET Image processing, 1(3): 311-318, 2007.

                        III.   Download matlab code of paper: Edge-detection-toolbox

                        Peng-lang Shui, Wei-Chuan Zhang, Noise-robust edge detector combining isotropic and anisotropic Gaussian kernels, Pattern Recognition, 45(2):806-820, 2012.

                        IV.   Download matlab code of paper: Corner-detection-toolbox

                        Peng-Lang Shui and Wei-Chuan Zhang,Corner Detection and Classification using Anisotropic Directional Derivative Representations, IEEE Trans. Image Processing, 22(8):3204-3218, Aug., 2013.

                        V.       Download matlab code of paper: SAR-edge-detection-toolbox

                        Peng-Lang Shui, Dong Cheng,Edge detector of SAR images using Gaussian-Gamma-shaped bi-windows, IEEE Geoscience and Remote Sensing Letters, 9(5):846-850, 2012.

                        VI.  Download matlab code of paper: Color-edge-detection-toolbox

                        Wang Fu-Ping and Shui Peng-Lang, Noise-robust color edge detector using gradient matrix and anisotropic Gaussian directional derivative matrix,” Pattern Recognition, 52(1):346-357, 2016.

                        VII.       Download matlab code of paper: Fast SAR image segmentation toolbox

                        Peng-Lang Shui and Ze-Jun Zhang, “Fast SAR image segmentation via merging cost with relative common boundary length penalty,” IEEE Trans. Geoscience and Remote Sensing, 52(10):6434-6448, 2014.

                         

                         

                                                                                                     II. 教學課件(數學建模理論與實驗)

                        1.第一講:數學建模基本要素

                        2.第二講:初等模型

                        3.第三講:單變量優化模型

                        4.第四講:多變量優化模型

                        5.第五講:線性規劃與二次規劃

                        6.第六講:概率模型

                        7.第七講:圖論與幾何模型

                        8.第八講:動力系統模型

                         

                              
                              

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