代码搜索：Labeled
找到约 414 项符合「Labeled」的源代码
代码结果 414
www.eeworm.com/read/314653/13562202
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/493294/6399861
m istarget.m
%ISTARGET true if the label is target
%
% I = ISTARGET(A)
%
% Returns true for the objects from dataset A which are labeled
% 'target'.
%
% I = ISTARGET(LABA)
%
% It also works when no da
www.eeworm.com/read/493294/6399875
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/492400/6422190
m istarget.m
%ISTARGET true if the label is target
%
% I = ISTARGET(A)
%
% Returns true for the objects from dataset A which are labeled
% 'target'.
%
% I = ISTARGET(LABA)
%
% It also works when no da
www.eeworm.com/read/478412/6717206
m zfindlabel.m
function Surface = zFindLabel(Label)
% zFindLabel - Finds a previously labeled surface in the Zemax DDE client lens.
%
% Example :
% LabeledSurface = zFindLabel(10)
%
% Finds the surface number
www.eeworm.com/read/400577/11572574
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/400576/11573442
m istarget.m
%ISTARGET true if the label is target
%
% I = ISTARGET(A)
%
% Returns true for the objects from dataset A which are labeled
% 'target'.
%
% I = ISTARGET(LABA)
%
% It also works when no da
www.eeworm.com/read/157453/11704438
out image.out
Enter image size
The input image is
0010000
0011000
0000100
0001100
1000100
1110000
1110000
The labeled image is
0020000
0022000
0000300
0003300
4000300
4440000
4440000
www.eeworm.com/read/255755/12057204
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT
www.eeworm.com/read/150905/12248259
m cnormc.m
%CNORMC Classifier normalisation for ML posterior probabilities
%
% W = CNORMC(W,A)
%
% INPUT
% W Classifier mapping
% A Labeled dataset
%
% OUTPUT
% W Scaled classifier mapping
%
% DESCRIPT