Sentence examples for performance of the verification system from inspiring English sources
Although, the PCA-based classifiers perform nearly 3 times worse than the LDA-based one, an interesting finding of this paper compared to our previous work [19] is that the performance of the verification system can be further improved by fusing the LDA- and PCA-based classifiers.
Overall, the results clearly demonstrate that the proposed similarity measure fusion considerably improves the performance of the face verification system.
In summary, it is clear that it is still pertinent to ask which classifiers provide useful information and how the expert scores should be fused to achieve the best possible performance of the face verification system.
Over the past few years, many approaches based on the use of Gaussian mixture models (GMM) in a GMM universal background model (GMM-UBM) framework [7] have been proposed to improve the performance of speaker verification system.
The rest of the time, undocumented workers will use documents that allow them to pass through the verification system.
The value where FPR = FNR is called equal error rate (EER) and is widely used to determine performance of a verification system as a single parameter.
In the experimental results, we will show out the performance of a fingerprint verification system by using the EER and ROC, respectively.
Traditional speech enhancement (SE) methods have been employed to improve the performance of speaker verification systems.
First, the performance of face verification systems in PCA and LDA feature spaces with different similarity measure classifiers was experimentally evaluated.
Similarly, the performance of writer verification systems is represented through receiver operating characteristic (ROC) curves and is quantified through area under the curve (AUC) or equal error rates (EER).
The performance of face verification systems using different similarity measures in two well-known appearance-based representation spaces, namely Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) is experimentally studied.
