The average performance comparison of the proposed scheme with other schemes for different values of T in terms of (a) bpp, (b) PSNR, and (c) SSIM.</p
Performance comparison of the proposed method with state-of-the-art methods on the Wang 10k dataset....
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>(a) The FNR and FPR Comparison of algorithms. And (b) the Performance Comparison of Algorithms.</...
<p>Performance comparison and relative gain of the proposed scheme over the existing schemes.</p
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Comparison of the classification performance by the proposed network and other methods.</p
<p>Performance comparison of the best DCBS and TTB systems with the different feature sets.</p
<p>Comparison of the average precision rates, recall rates and F1 values for the different classific...
<p>Computational times and accuracy comparisons of various algorithms on Schemes 1–4.</p
<p>Performance comparison of the proposed algorithm and 17 existing algorithms using four existing e...
Performance comparison of the proposed method with state-of-the-art methods on the Wang-B dataset.</...
<p>The performance of different methods in terms of in terms of Se, Sp, Acc and Auc.</p
Comparing performance of the proposed methods built with different number of individual models.</p
<p>The symbol “1”, “−”, or “0” means that the proposed scheme statistically (with 95% confidence) be...
<p>Comparison between our scheme and some typical (<i>k</i>, <i>n</i>)-SIS schemes.</p
Performance comparison of the proposed method with state-of-the-art methods on the Wang 10k dataset....
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>(a) The FNR and FPR Comparison of algorithms. And (b) the Performance Comparison of Algorithms.</...
<p>Performance comparison and relative gain of the proposed scheme over the existing schemes.</p
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
Comparison of the classification performance by the proposed network and other methods.</p
<p>Performance comparison of the best DCBS and TTB systems with the different feature sets.</p
<p>Comparison of the average precision rates, recall rates and F1 values for the different classific...
<p>Computational times and accuracy comparisons of various algorithms on Schemes 1–4.</p
<p>Performance comparison of the proposed algorithm and 17 existing algorithms using four existing e...
Performance comparison of the proposed method with state-of-the-art methods on the Wang-B dataset.</...
<p>The performance of different methods in terms of in terms of Se, Sp, Acc and Auc.</p
Comparing performance of the proposed methods built with different number of individual models.</p
<p>The symbol “1”, “−”, or “0” means that the proposed scheme statistically (with 95% confidence) be...
<p>Comparison between our scheme and some typical (<i>k</i>, <i>n</i>)-SIS schemes.</p
Performance comparison of the proposed method with state-of-the-art methods on the Wang 10k dataset....
<p>Performance comparison of the first experiment (results of our proposed algorithm are in bold).</...
<p>(a) The FNR and FPR Comparison of algorithms. And (b) the Performance Comparison of Algorithms.</...
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