## 3 Analysis and Results of CGAN-IFCM
### Performance Evaluation of CGAN-IFCM
#### 3.1.2 Multi-Class Detection Model using CGAN-IFCM
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Control Weighting Factors**} & \multicolumn{6}{c}{**TNR (\%)/TPR (\%) with Varying \(N_{c}\)**} \\ \hline \hline \(\omega_{n}\) & \(\omega_{0}\) & **3** & **4** & **5** & **6** & **7** & **8** & **9** & **10** \\ \hline \multirow{8}{*}{2} & 2 & 83.2/79.6 & 84.3/80.0 & 85.6/80.8 & 86.1/81.9 & 90.3/86.3 & 89.2/85.1 & 86.0/83.6 & 83.8/79.5 \\ \cline{2-10}  & 2.1 & 82.2/78.7 & 83.0/79.1 & 83.5/79.6 & 84.4/80.3 & 87.8/84.6 & 87.0/83.8 & 85.4/82.5 & 81.2/77.7 \\ \cline{2-10}  & 2.2 & 81.2/77.0 & 82.0/77.9 & 82.6/78.7 & 83.4/79.8 & 85.7/83.6 & 83.6/81.4 & 83.8/80.2 & 80.1/76.8 \\ \cline{2-10}  & 2.3 & 79.8/75.9 & 80.6/76.8 & 81.6/77.9 & 82.2/78.4 & 84.8/81.8 & 82.1/80.1 & 82.3/79.4 & 79.7/75.3 \\ \cline{2-10}  & 2.4 & 78.9/75.5 & 80.0/75.7 & 80.3/76.5 & 81.3/77.5 & 83.7/80.6 & 81.7/78.6 & 81.1/78.5 & 78.3/74.3 \\ \hline \multirow{8}{*}{2.1} & 2 & 85.4/80.3 & 86.2/81.2 & 87.0/82.3 & 88.2/84.6 & 91.2/86.8 & 89.9/85.5 & 88.3/84.9 & 86.1/82.6 \\ \cline{2-10}  & 2.1 & 84.2/79.5 & 85.4/80.6 & 86.3/81.4 & 87.4/83.2 & 90.3/85.6 & 89.5/84.7 & 87.6/83.1 & 85.3/81.3 \\ \cline{2-10}  & 2.2 & 83.6/78.7 & 84.3/80.0 & 85.2/80.3 & 86.3/82.3 & 89.5/84.2 & 88.6/83.6 & 87.1/82.3 & 84.4/80.5 \\ \cline{2-10}  & 2.3 & 82.5/77.7 & 83.2/79.1 & 84.1/79.7 & 85.3/81.6 & 88.8/83.1 & 87.5/82.6 & 86.3/81.2 & 83.2/79.8 \\ \cline{2-10}  & 2.4 & 81.3/76.9 & 82.4/78.1 & 83.4/78.7 & 84.5/80.9 & 86.3/82.0 & 84.9/81.3 & 84.1/80.5 & 82.3/79.1 \\ \hline \multirow{8}{*}{2.2} & 2 & 86.1/81.8 & 87.2/82.5 & 88.2/84.0 & 89.3/85.6 & 91.6/87.6 & 90.3/86.4 & 88.9/85.3 & 87.6/84.1 \\ \cline{2-10}  & 2.1 & 85.2/80.5 & 86.0/81.3 & 87.1/83.5 & 88.0/84.2 & 90.3/86.3 & 89.6/85.0 & 87.8/84.1 & 86.4/83.7 \\ \cline{2-10}  & 2.2 & 84.3/79.6 & 85.3/80.7 & 86.3/82.0 & 87.2/83.6 & 89.6/85.5 & 88.8/84.3 & 86.3/83.2 & 85.6/82.7 \\ \cline{2-10}  & 2.3 & 83.4/78.7 & 84.6/79.9 & 85.6/80.9 & 86.4/82.8 & 89.1/84.6 & 88.5/83.8 & 85.5/82.6 & 84.8/81.2 \\ \cline{2-10}  & 2.4 & 81.5/77.9 & 82.6/79.2 & 83.3/80.0 & 83.8/81.8 & 87.5/83.8 & 86.8/82.6 & 85.0/81.3 & 83.6/80.8 \\ \hline \multirow{8}{*}{2.3} & 2 & 87.6/82.1 & 88.5/83.4 & 89.4/85.3 & 90.6/85.9 & 92.1/88.5 & 90.4/86.9 & 89.7/86.2 & 88.8/85.3 \\ \cline{2-10}  & 2.1 & 86.3/81.3 & 87.6/82.8 & 88.5/84.5 & 88.8/84.8 & 91.2/87.3 & 90.0/85.8 & 88.7/85.1 & 87.2/84.6 \\ \cline{1-1} \cline{2-10}  & 2.2 & 85.4/80.1 & 86.2/81.3 & 87.3/83.6 & 86.3/84.1 & 90.2/86.6 & 89.3/85.3 & 87.2/84.1 & 86.6/83.5 \\ \cline{1-1} \cline{2-10}  & 2.3 & 84.6/79.6 & 85.8/80.5 & 86.2/81.3 & 85.3/83.6 & 89.7/85.3 & 89.0/84.2 & 86.0/83.5 & 85.2/82.6 \\ \cline{1-1} \cline{2-10}  & 2.4 & 82.5/79.3 & 83.1/80.5 & 83.8/81.5 & 84.3/82.5 & 88.8/84.3 & 87.8/83.6 & 86.3/82.6 & 83.9/81.2 \\ \hline \multirow{8}{*}{2.4} & 2 & 84.5/80.0 & 85.8/81.3 & 87.1/82.6 & 88.4/83.5 & 90.2/86.1 & 87.3/84.8 & 85.1/83.7 & 83.6/82.4 \\ \cline{1-1} \cline{2-10}  & 2.1 & 83.8/79.1 & 85.0/81.2 & 86.0/81.4 & 87.1/82.3 & 89.6/85.2 & 86.6/83.1 & 84.0/82.5 & 82.3/81.5 \\ \cline{1-1} \cline{2-10}  & 2.2 & 82.4/78.0 & 83.5/79.5 & 84.2/80.3 & 85.1/81.6 & 88.2/84.5 & 85.8/82.2 & 82.6/81.7 & 81.0/80.4 \\ \cline{1-1} \cline{2-10}  & 2.3 & 81.3/77.7 & 82.4/78.7 & 83.5/79.6 & 84.7/80.8 & 86.8/83.2 & 84.9/81.6 & 81.1/80.8 & 80.1/79.8 \\ \cline{1-1} \cline{2-10}  & 2.4 & 80.4/76.3 & 81.5/77.5 & 82.0/78.5 & 83.2/79.4 & 85.6/81.3 & 83.6/80.3 & 80.2/78.1 & 79.6/76.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance evaluation of the multi-class detection model using CGAN-IFCM while varying \(N_{c}\), \(\omega_{n}\), and \(\omega_{0}\) with the SVD database. (a) Fixed \(\omega_{n}=1.8\). (b) Fixed \(\omega_{n}=1.9\). (c) Fixed \(\omega_{n}=2.0\). (d) Fixed \(\omega_{n}=2.1\). (e)