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Additionally, we provide the overall performance using different classifiers and luminance filters.
The present work aims to simplify the model and strengthen these results by comparing only the MFS with other state-of-the-art features and using different classifiers and also to study the correlations of the features obtained with the procedure and different texture features obtained from the images.
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We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme.
Although LMHI did not perform as well as other methods (72.7%), there may be room for improvement by supplementing it with additional feature descriptors and using different classifiers.
Using different classifiers trained on the annotated corpus, Precision and F1 improved while recall decreased.
Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers.
Finally, we provide a performance evaluation at pixel level using different classifiers.
Third, we investigate the overall performance of the approach using different classifiers in Section 5.3.
Figure 8 Evaluation of HTER with LBP-TOP 8, 8, 8, 1, 1, R t u 2 using different classifiers.
Algorithm 1 represents singer recognition approach using different classifiers from IS. Algorithm 1 Singer recognition approach 1. Collection of N Indian video songs of M singers.
From the average classification accuracy found on different feature selection methods using different classifiers, we observed that decision tree, random forest, KNN and SVM yield high classification accuracy than other feature selection methods.
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