# Fine-Tuning of Pre-Trained Deep Face Sketch Models Using Smart Switching Slime Mold Algorithm
## 4 Experimental Results and Analysis
### Evaluation on Large-Scale Benchmark Problems (CEC'2010)
#### 4.1.3 Convergence Evaluation
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Function**} & \multirow{2}{*}{**Fitness**} & \multicolumn{5}{c}{**Algorithm**} \\ \cline{3-8}  & & \multicolumn{2}{c}{**S\({}^{2}\)SMA**} & \multirow{2}{*}{**SMA**} & \multirow{2}{*}{**ESMA**} & \multirow{2}{*}{**LASMA**} & \multirow{2}{*}{**AOSMA**} & \multirow{2}{*}{**AOA**} \\ \cline{3-8}  & & **(Proposed)** & & & & & \\ \hline \multirow{5}{*}{F1} & Best & 1.76 \(\times\)\(10^{9}\) & 7.81 \(\times\)\(10^{9}\) & 5.14 \(\times\)\(10^{9}\) & 1.11 \(\times\)\(10^{10}\) & 1.57 \(\times\)\(10^{10}\) & 1.77 \(\times\)\(10^{11}\) \\ \cline{2-8}  & Median & 2.06 \(\times\)\(10^{9}\) & 9.14 \(\times\)\(10^{9}\) & 6.03 \(\times\)\(10^{9}\) & 1.4 \(\times\)\(10^{10}\) & 1.88 \(\times\)\(10^{10}\) & 1.88 \(\times\)\(10^{11}\) \\ \cline{2-8}  & Worst & 2.61 \(\times\)\(10^{9}\) & 1.05 \(\times\)\(10^{10}\) & 6.89 \(\times\)\(10^{9}\) & 1.54 \(\times\)\(10^{10}\) & 2.27 \(\times\)\(10^{10}\) & 1.98 \(\times\)\(10^{11}\) \\ \cline{2-8}  & Mean & **2.07 \(\times\)\(10^{9}\)** & 9.17 \(\times\)\(10^{9}\) & 5.95 \(\times\)\(10^{9}\) & 1.37 \(\times\)\(10^{10}\) & 1.87 \(\times\)\(10^{10}\) & 1.88 \(\times\)\(10^{11}\) \\ \cline{2-8}  & Std & 1.98 \(\times\)\(10^{8}\) & 7.18 \(\times\)\(10^{8}\) & 4.63 \(\times\)\(10^{8}\) & 1 \(\times\)\(10^{9}\) & 1.85 \(\times\)\(10^{9}\) & 4.99 \(\times\)\(10^{9}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of 1000-D CEC’2010 large-scale functions. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Function**} & \multicolumn{5}{c}{**Algorithm**} \\ \cline{2-5}  & **Proposed\_30** & **Proposed\_10** & **Proposed\_30** & **Proposed\_10** \\ \cline{2-5}  & **Mean** & **Mean** & **Std.** & **Std.** \\ \hline F1 & **8.8 \(\times\)\(10^{9}\)** & 2.26 \(\times\)\(10^{10}\) & 6.57 \(\times\)\(10^{8}\) & 1.58 \(\times\)\(10^{9}\) \\ \hline F2 & **12,129.97** & 13,175.47 & 198.788 & 219.3744 \\ \hline F3 & **20.97428** & 20.98415 & 0.014797 & 0.016608 \\ \hline F4 & **3.82 \(\times\)\(10^{13}\)** & 6.92 \(\times\)\(10^{13}\) & 1.32 \(\times\)\(10^{13}\) & 1.93 \(\times\)\(10^{13}\) \\ \hline F5 & **2.71 \(\times\)\(10^{8}\)** & 3.45 \(\times\)\(10^{8}\) & 55,552,821 & 91,773,918 \\ \hline F6 & **5,113,851** & 11,026,896 & 4,929,368 & 6,083,478 \\ \hline F7 & **5.69 \(\times\)\(10^{9}\)** & 2.32 \(\times\)\(10^{10}\) & 1.51 \(\times\)\(10^{9}\) & 4.59 \(\times\)\(10^{9}\) \\ \hline F8 & **1.37 \(\times\)\(10^{9}\)** & 1.04 \(\times\)\(10^{10}\) & 2.59 \(\times\)\(10^{9}\) & 1.18 \(\times\)\(10^{10}\) \\ \hline F9 & **1.14 \(\times\)\(10^{10}\)** & 2.47 \(\times\)\(10^{10}\) & 5.67 \(\times\)\(10^{8}\) & 1.99 \(\times\)\(10^{9}\) \\ \hline F10 & **12,130.43** & 13,041.73 & 178.6562 & 185.0105 \\ \hline F11 & **227,1399** & 228.2753 & 0.659421 & 0.635519 \\ \hline F12 & **3,809,917** & 4,223,945 & 189,280.9 & 230,020.6 \\ \hline F13 & **3.76 \(\times\)\(10^{9}\)** & 5.52 \(\times\)\(10^{10}\) & 6.97 \(\times\)\(10^{8}\) & 8.12 \(\times\)\(10^{9}\) \\ \hline F14 & **1.28 \(\times\)\(10^{10}\)** & 2.6 \(\times\)\(10^{10}\) & 1.25 \(\times\)\(10^{9}\) & 2.09 \(\times\)\(10^{9}\) \\ \hline F15 & **12,230.97** & 13,068.63 & 189.9647 & 222.852 \\ \hline F16 & **412,4328** & 414.7671 & 0.712702 & 0.882251 \\ \hline F17 & **4,775,455** & 5,446,786 & 316,617.3 & 457,231.5 \\ \hline F18 & **1.25 \(\times\)\(10^{11}\)** & 4.27 \(\times\)\(10^{11}\) & 1.46 \(\times\)\(10^{10}\) & 2.98 \(\times\)\(10^{10}\) \\ \hline F19 & **13,908,503** & 19,032,212 & 1,323,228 & 1,332,130 \\ \hline F20 & **1.52 \(\times\)\(10^{11}\)** & 5.05 \(\times\)\(10^{11}\) & 1.26 \(\times\)\(10^{10}\) & 3.31 \(\times\)\(10^{10}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of S\({}^{2}\)SMA (proposed) with 10 and 30 search agents.