Description: （压缩包里一共有5个代码）
pca+lda+粗糙集+模糊神经网络
saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat
1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat
2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat
3.将disdata组成决策表(savers.m)，通过对disdata的条件属性进行约简，得到其一个约简，组成新的测试集rstest和训练集rsstudy存为imagersdata.mat
4.对rsstudy进行模糊神经网络训练(savecul.m)，对模糊神经网络的参数进行调整学习将其存入culdata.mat
5.用runfnn.m对rstest进行测试得到其识别率
savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.-pca+ lda+ Rough Set+ fuzzy neural network
saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat
Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat
2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat
3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat
4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat
5. Rstest used to test for runfnn.m by its recognition rate
cm.m is savem.m and minimum distance classifier on the training set and test set classificati Platform: |
Size: 2048 |
Author:dong |
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Description: 用gabor 来做特征提取，用神经元网络来分类的人脸检测代码，配有详细的代码解释，适合初学者-use gabor for feature extraction,use neural network as a classifier to detect face in a image Platform: |
Size: 2068480 |
Author:xiang |
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Description: 结合DCT和BP神经网络进行人脸识别。先利用DCT提取特征，然后利用BP神经网络分类，在ORL人脸库上测试效果不错。-The combination of DCT and BP neural network for face recognition. First DCT Feature Extraction, and then use the BP neural network classifier, a good test results on the ORL face database. Platform: |
Size: 2048 |
Author:尹贺峰 |
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Description: 以BP算法和RRA理论为基础，采用BP_RRA作为人脸识别分类器，结合归一化伪zernike矩，提出一种基于归一化伪zernike矩和BP_RRA神经网络的人脸识别算法。-BP algorithm and the RRA theory, based on the normalized pseudo-zernike moments BP_RRA as face recognition classifier combined to propose a face recognition algorithm based on normalized of pseudo zernike of moments and the BP_RRA neural network.
Platform: |
Size: 1112064 |
Author:洁洁 |
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Description: Nowadays security becomes a most important issue regarding a spoof attack. So, multimodal biometrics technology has attracted
substantial interest for its highest user acceptance, high security, high accuracy, low spoof attack and high recognition
performance in biometric recognition system. This multimodal biometrics system introduces recognition of person from two
things i.e. face & palm print. Principal Component Analysis (PCA) algorithm is used for reduction of dimension & extraction of
features in terms of eigenvalues & eigenvectors. Feature level fusion technique used to fuse the results of face & palm prints and
then gives the output as per neural network classifier which gives the correct information about genuine or imposter identity. Platform: |
Size: 282624 |
Author:atish |
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Search - neural network face classifier