x = reshape(result_img,[r*c b]); x = compute_mapping(x,'PCA',1); % 对原图进行PCA降维 guidance = reshape(x, r, c)/255; % 获得引导图像 result_img = double(result_img)/255; r = 5; % 滤波半径 eps = 0.005; % 滤波正则化参数 for i = 1:3 result_img_GD(:,:,i) = guide...
这些技术都可以通过COMPUTE_MAPPING函数或trhough GUI。有以下技术可用: - 主成分分析('PCA') - 线性判别分析('LDA') - 多维缩放('MDS') - 概率PCA('ProbPCA') - 因素分析('因子分析') - Sammon映射('Sammon') - Isomap('Isomap') - Landmark Isomap('LandmarkIsomap') - 局部线性嵌入('LLE') - ...
scatter(mappedX(:,1), mappedX(:,2), 5, labels(mapping.conn_comp)) title('Result of Laplacian Eigenmaps') drawnow % Isomap降维 [mappedX, mapping] = compute_mapping(X, 'Isomap', no_dims); figure scatter(mappedX(:,1), mappedX(:,2), 5, labels(mapping.conn_comp)) title('Result o...
之后在Matlab工作环境中,只需要运行compute_mapping命令即可使用工具箱中的函数,如: mappedX = compute_mapping(X, 'PDA', 1); 具体参加说明文档。 在使用‘Isomap’算法时,会遇到错误如下: Invalid MEX-file C:\Program Files\MATLAB\R2010b\toolbox\drtoolbox\techniques\dijkstra.dll 找不到指定模块 发现相应...
end; % compute, select & normalize eigenvalues [V, D] = eig(cov([M1(:) M2(:)])); if (D(1,1) > D(2,2)) a = V(:,1)./sum(V(:,1)); else a = V(:,2)./sum(V(:,2)); end; % and fuse Y = a(1)*M1+a(2)*M2; 5.2.3 金字塔(Pyramid)算法程序 ...
接着进入到均匀化步骤,首先判断是否是图像增强,这里是,其次调用computeCumulativeHistogram函数来得到均匀化后矩阵,最后调用grayxformmex来进行颜色的匹配,computeCumulativeHistogram函数来得到均匀化后矩阵,最后调用grayxformmex来进行颜色的匹配。 % Intensity image or indexed imageifisIntensityImage ...
固定步长大小降采样只能在随机或非均匀网格采样模式下才能使用。 降采样点云与使用固定步长大小降采样的数据进行比较: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 stepSize=floor(ptCloud.Count/ptCloudA.Count);indices=1:stepSize:ptCloud.Count;ptCloudB=select(ptCloud,indices); ...
[r*c b]); x = compute_mapping(x,'PCA',1); % 对原图进行PCA降维 guidance = reshape(x, r, c)/255; % 获得引导图像 result_img = double(result_img)/255; r = 5; % 滤波半径 eps = 0.005; % 滤波正则化参数 for i = 1:3 result_img_GD(:,:,i) = guidedfilter(guidance, result_...
This MATLAB function returns the gradient-weighted class activation mapping (Grad-CAM) map of the change in the classification score of input X, when the network net evaluates the class score for the class given by classIdx.
For example, if you are using compiler.build.dotNETAssembly, type: cmap = containers.Map; cmap('SignalAnalyzer') = 'computefft.m'; cmap('Plotter') = 'plotfft'; buildResults = compiler.build.dotNETAssembly(cmap, ... 'AssemblyName','SpectraComp'); For more details, see the instructions ...