91av视频/亚洲h视频/操亚洲美女/外国一级黄色毛片 - 国产三级三级三级三级

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    發布日期: 2023-09-25
  • 語言: Html/CSS
  • 標簽: PCA??adaboost??svm??

資源簡介

本文使用了ORL人臉數據庫,訓練樣本為40人,每人5張圖片,共計200張圖片,圖片大小為92*122。測試樣本為40人,每人5張圖片共計200張圖片,圖片大小為92*122。ORL數據庫可以從http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html得到。如果只是以隨機選擇的方式來識別某個人的身份的話,從概率角度來說識別率僅為2.5%,我們的任務是如何使識別率突破50%或者更高,這是個艱巨的任務。從訓練角度來看,我們需要處理40*5*92*112=2060800個像素點,這是個維度災難。針對以上問題,本文提出了PCA+SVM+一對一投票策略與PCA+Adaboost+一對一投票策略來解決上述問題,達到了良好的效果,使測試樣本的識別率分別達到了84%與52.5%。

資源截圖

代碼片段和文件信息

function?[Lhits]?=?ADABOOST_te(adaboost_modelte_func_handletest_settrue_labels)
%
%?ADABOOST?TESTING
%
%??[Lhits]?=?ADABOOST_te(adaboost_modelte_func_handletrain_set
%?????????????????????????true_labels)
%
%???????????‘te_func_handle‘?is?a?handle?to?the?testing?function?of?a
%???????????learning?(weak)?algorithm?whose?prototype?is?shown?below.
%
%???????????[Lhitserror_rate]?=?test_func(modeltest_setsample_weightstrue_labels)
%????????????????????model:?the?output?of?train_func
%????????????????????test_set:?a?KxD?dimensional?matrix?each?of?whose?row?is?a
%????????????????????????testing?sample?in?a?D?dimensional?feature?space.
%????????????????????sample_weights:??a?Dx1?dimensional?vector?the?i-th?entry?
%????????????????????????of?which?denotes?the?weight?of?the?i-th?sample.
%????????????????????true_labels:?a?Dx1?dimensional?vector?the?i-th?entry?of?which
%????????????????????????is?the?label?of?the?i-th?sample.
%????????????????????L:?a?Dx1-array?with?the?predicted?labels?of?the?samples.
%????????????????????hits:?number?of?hits?calculated?with?the?comparison?of?L?and
%????????????????????????true_labels.
%????????????????????error_rate:?number?of?misses?divided?by?the?number?of?samples.
%
%???????????It?is?the?corresponding?testing?
%???????????module?of?the?function?that?is?specified?in?the?training?phase.
%???????????‘test_set‘?is?a?NxD?matrix?where?N?is?the?number?of?samples
%???????????in?the?test?set?and?D?is?the?dimension?of?the?feature?space.
%???????????‘true_labels‘?is?a?Nx1?matrix?specifying?the?class?label?of
%???????????each?corresponding?sample‘s?features?(each?row)?in?‘test_set‘.
%???????????‘adaboost_model‘?is?the?model?that?is?generated?by?the?function
%???????????‘ADABOOST_tr‘.
%
%???????????‘L‘?is?the?likelihoods?that?are?assigned?by?the?‘ADABOOST_te‘.
%???????????‘hits‘?is?the?number?of?correctly?predicted?labels.
%
%????????Specific?Properties?That?Must?Be?Satisfied?by?The?Function?pointed
%????????by?‘func_handle‘
%????????------------------------------------------------------------------


hypothesis_n?=?length(adaboost_model.weights);
sample_n?=?size(test_set1);
if?nargin==4
????class_n?=?length(unique(true_labels));
????temp_L?=?zeros(sample_nclass_nhypothesis_n); %?likelihoods?for?each?weak?classifier

????%?for?each?weak?classifier?likelihoods?of?test?samples?are?collected
????for?i=1:hypothesis_n
????????[temp_L(::i)hitserror_rate]?=?te_func_handle(adaboost_model.parameters{i}...
?test_setones(sample_n1)true_labels);
????????temp_L(::i)?=?temp_L(::i)*adaboost_model.weights(i);
????end

????L?=?sum(temp_L3);
????hits?=?sum(likelihood2class(L)==true_labels);
else
????class_n=2;
????temp_L?=?zeros(sample_nclass_nhypothesis_n); %?likelihoods?for?each?weak?classifier

????%?for?each?weak?classifier?likelihoods?of?test?samples?are?collected
????for?i=1:hypothesis_n
????????temp_L(::i)?=?te_func_handle(adaboost_model.parameters{i}...
?test_setones(sampl

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????3152??2011-01-26?20:39??基于matlab的人臉識別系統\FaceRec\ADABOOST_te.m

?????文件???????4115??2011-01-26?20:40??基于matlab的人臉識別系統\FaceRec\ADABOOST_tr.m

?????文件????????354??2009-01-01?18:20??基于matlab的人臉識別系統\FaceRec\approx.m

?????文件???????1366??2011-01-25?16:41??基于matlab的人臉識別系統\FaceRec\classify.m

?????文件?????207960??2012-03-26?21:04??基于matlab的人臉識別系統\FaceRec\composite.tiff

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s1\1.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s1\2.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s1\3.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s1\4.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s1\5.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s10\1.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s10\2.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s10\3.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s10\4.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s10\5.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s11\1.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s11\2.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s11\3.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s11\4.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s11\5.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s12\1.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s12\2.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s12\3.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s12\4.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s12\5.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s13\1.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s13\2.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s13\3.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s13\4.pgm

?????文件??????10318??2007-10-30?06:16??基于matlab的人臉識別系統\FaceRec\Data\sample\s13\5.pgm

............此處省略495個文件信息

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