代码搜索：Pattern recognition
找到约 10,000 项符合「Pattern recognition」的源代码
代码结果 10,000
www.eeworm.com/read/271333/11000041
m image recognition.m
clear all
clc
NumOfImage = 34;
width=32;
hight=32;
for i = 1: NumOfImage
% i
R=imread(num2str(i),'bmp');
B=(R(:))';
v(i,:)=double(B);
vmean(i)=mean(i,:);
v(i,:)=v(i,:)-mean
www.eeworm.com/read/450195/7488973
m recognition_svm.m
clear all;
close all;
x1(1,1)=5.1418; x1(1,2)=0.5950;
x1(2,1)=5.5519; x1(2,2)=3.5091;
x1(3,1)=5.3836; x1(3,2)=2.8033;
x1(4,1)=3.2419; x1(4,2)=3.7278;
x1(5,1)=4.4427; x1(5,2)=3.8981;
x1(6,1)=4
www.eeworm.com/read/445465/7595282
exe text recognition.exe
www.eeworm.com/read/445465/7595284
vbp text recognition.vbp
Type=Exe
Reference=*\G{00020430-0000-0000-C000-000000000046}#2.0#0#C:\WINDOWS\system32\stdole2.tlb#OLE Automation
Object={F9043C88-F6F2-101A-A3C9-08002B2F49FB}#1.2#0; COMDLG32.OCX
Object={831FDD16-
www.eeworm.com/read/445465/7595286
vbw text recognition.vbw
recMain = 50, 38, 425, 384, Z
frmMain = 15, 8, 752, 289, , 110, 110, 485, 456, C
frmSplash = 110, 110, 574, 391, , 132, 132, 507, 478, C
frmLogin = 174, 41, 549, 387, , 22, 32, 397, 378, C
frmAbou
www.eeworm.com/read/445465/7595288
pdm text recognition.pdm
[Root]
Most Recent Package=Text Recognition Software
Most Recent Deploy=Text Recognition Software
[Package|Text Recognition|Root]
SubWizProgID=PDWizard.SetupPkgSubWiz
BuildFolder=C:\Program F
www.eeworm.com/read/440480/7688857
m recognition_demo.m
% Describes all steps of behavior recognition; example for facial expressions.
%
% The file describes the following:
% 1) data format [3 choices]
% 2) feature detection & description [2 choices]
%
www.eeworm.com/read/435094/7797365
m face_recognition.m
clear all;
%% Face recognition
% This algorithm uses the eigenface system (based on pricipal component
% analysis - PCA) to recognize faces. For more information on this method
% refer to http://c
www.eeworm.com/read/295921/8134737
m face_recognition.m
%% Face recognition
% This algorithm uses the eigenface system (based on pricipal component
% analysis - PCA) to recognize faces. For more information on this method
% refer to http://cnx.org/conte