<p>Top-left represents the relation between the rank of first class face matrix and the number of iterations on Yale B Face Database with 40 training samples. Top-right, bottom-left and bottom-right represent that of second, third and forth class face matrices, respectively.</p
Nonparametric statistics for quantifying dependence between the output rankings of face recognition ...
<p>A) The upper matrix reports the number of DMSs between two BSseq replicates. The lower matrix rep...
<p>The recognition rates (%) of five different face recognition methods on the datasets Yale_32×32 a...
<p>Each column of matrix represents a eigenface, and each sample (column) in face matrix can be re...
<p>Relationships between the number of training samples and the F1 value for the different classific...
<p>Performance comparison on the Yale face database (results of our proposed algorithm are in bold)....
<p>Trainees' performance over the courses of training for face memory (Panel A) and for facial speed...
<p>The data presented in each column is the probability of the participants' judgments. The recognit...
The data matrix of the face dataset: 6 faces by 55,200 voxels. The female faces are denoted F1, F2, ...
<p>The relationship between the master matrix and the four auxiliary matrices.</p
<p>The matching matrix between results of smear and machine 5-level grading for AO stained direct sm...
<p>(a) CMU-PIE database (b) Yale B database (c) 3D face database (d) Yale database.</p
<p>Contact matrices giving the cumulated durations of contacts (1st line), the number of contacts (2...
<p>Performance comparison on the FERET face database (results obtained with our proposed algorithm a...
<p>Correlation matrices for Experiment 1a (above diagonal) and Experiment 1b (below diagonal).</p
Nonparametric statistics for quantifying dependence between the output rankings of face recognition ...
<p>A) The upper matrix reports the number of DMSs between two BSseq replicates. The lower matrix rep...
<p>The recognition rates (%) of five different face recognition methods on the datasets Yale_32×32 a...
<p>Each column of matrix represents a eigenface, and each sample (column) in face matrix can be re...
<p>Relationships between the number of training samples and the F1 value for the different classific...
<p>Performance comparison on the Yale face database (results of our proposed algorithm are in bold)....
<p>Trainees' performance over the courses of training for face memory (Panel A) and for facial speed...
<p>The data presented in each column is the probability of the participants' judgments. The recognit...
The data matrix of the face dataset: 6 faces by 55,200 voxels. The female faces are denoted F1, F2, ...
<p>The relationship between the master matrix and the four auxiliary matrices.</p
<p>The matching matrix between results of smear and machine 5-level grading for AO stained direct sm...
<p>(a) CMU-PIE database (b) Yale B database (c) 3D face database (d) Yale database.</p
<p>Contact matrices giving the cumulated durations of contacts (1st line), the number of contacts (2...
<p>Performance comparison on the FERET face database (results obtained with our proposed algorithm a...
<p>Correlation matrices for Experiment 1a (above diagonal) and Experiment 1b (below diagonal).</p
Nonparametric statistics for quantifying dependence between the output rankings of face recognition ...
<p>A) The upper matrix reports the number of DMSs between two BSseq replicates. The lower matrix rep...
<p>The recognition rates (%) of five different face recognition methods on the datasets Yale_32×32 a...
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