## 3 The Proposed Model
### Loss Function
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Train Dataset**} & \multirow{2}{*}{**Test Dataset**} & \multicolumn{4}{c}{**De-Test B**} & \multicolumn{4}{c}{**De-Test C**} \\ \cline{3-10}  & & & **DDA** & **DDR** & **FDR** & **DDA** & **DDR** & **FDR** \\ \hline \multirow{4}{*}{SSD} & \multirow{4}{*}{De-Train B} & Tree-CycleGAN [42] & 89.01\% & 74.19\% & 8.00\% & 89.56\% & 75.81\% & 7.84\% \\  & & CycleGAN-TSS [43] & 89.56\% & 74.19\% & 6.12\% & 90.11\% & 75.81\% & 6.00\% \\  & & PreCaCycleGAN & **91.30\%** & **78.13\%** & **3.85\%** & **91.80\%** & **79.37\%** & **3.85\%** \\ \cline{2-10}  & \multirow{4}{*}{De-Train C} & Tree-CycleGAN [42] & 91.16\% & 75.41\% & 2.13\% & 92.82\% & 80.33\% & 2.00\% \\  & & CycleGAN-TSS [43] & 91.26\% & 76.19\% & 2.04\% & 92.86\% & 80.65\% & 1.96\% \\  & & PreCaCycleGAN & **93.05\%** & **80.60\%** & **0.00\%** & **94.05\%** & **83.08\%** & **0.00\%** \\ \hline \hline \multirow{4}{*}{Faster-RCNN} & \multirow{4}{*}{De-Train B} & Tree-CycleGAN [42] & 91.76\% & 80.65\% & 5.66\% & 92.31\% & 82.26\% & 5.56\% \\  & & CycleGAN-TSS [43] & 91.76\% & 79.03\% & 3.92\% & 92.86\% & 82.26\% & 3.77\% \\  & & PreCaCycleGAN & **92.93\%** & **81.25\%** & **1.89\%** & **93.99\%** & **84.13\%** & **1.85\%** \\ \cline{2-10}  & \multirow{4}{*}{De-Train C} & Tree-CycleGAN [42] & 93.37\% & 81.97\% & 1.96\% & 95.03\% & 86.89\% & 1.85\% \\ \cline{2-10}  & & CycleGAN-TSS [43] & 93.99\% & 82.54\% & 0.00\% & 95.60\% & 87.10\% & 0.00\% \\  & & PreCaCycleGAN & **95.19\%** & **86.57\%** & **0.00\%** & **96.22\%** & **89.23\%** & **0.00\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 11: _Cont._ \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Train Dataset**} & \multirow{2}{*}{**Test Dataset**} & \multicolumn{4}{c}{**De-Test B**} & \multicolumn{4}{c}{**De-Test C**} \\ \cline{3-10}  & & & **DDA** & **DDR** & **FDR** & **DDA** & **DDR** & **FDR** \\ \hline \multirow{4}{*}{YOLOv5} & \multirow{4}{*}{De-Train B} & Tree-CycleGAN [42] & 89.01\% & 74.19\% & 8.00\% & 89.56\% & 75.81\% & 7.84\% \\  & & CycleGAN-TSS [43] & 89.56\% & 74.19\% & 6.12\% & 90.11\% & 75.81\% & 6.00\% \\  & & PreCaCycleGAN & **91.30\%** & **78.13\%** & **3.85\%** & **91.80\%** & **79.37\%** & **3.85\%** \\ \cline{2-10}  & \multirow{4}{*}{De-Train C} & Tree-CycleGAN [42] & 91.16\% & 75.41\% & 2.13\% & 92.82\% & 80.33\% & 2.00\% \\  & & CycleGAN-TSS [43] & 91.26\% & 76.19\% & 2.04\% & 92.86\% & 80.65\% & 1.96\% \\  & & PreCaCycleGAN & **93.05\%** & **80.60\%** & **0.00\%** & **94.05\%** & **83.08\%** & **0.00\%** \\ \hline \hline \multirow{4}{*}{Faster-RCNN} & \multirow{4}{*}{De-Train B} & Tree-CycleGAN [42] & 91.76\% & 80.65\% & 5.66\% & 92.31\% & 82.26\% & 5.56\% \\  & & CycleGAN-TSS [43] & 91.76\% & 79.03\% & 3.92\% & 92.86\% & 82.26\% & 3.77\% \\ \cline{1-1}  & & PreCaCycleGAN & **92.93\%** & **81.25\%** & **1.89\%** & **93.99\%** & **84.13\%** & **1.85\%** \\ \cline{1-1} \cline{2-10}  & \multirow{4}{*}{De-Train C} & Tree-CycleGAN [42] & 93.37\% & 81.97\% & 1.96\% & 95.03\% & 86.89\% & 1.85\% \\ \cline{1-1}  & & CycleGAN-TSS [43] & 93.99\% & 82.54\% & 0.00\% & 95.60\% & 87.10\% & 0.00\% \\ \cline{1-1}  & & PreCaCycleGAN & **95.19\%** & **86.57\%** & **0.00\%** & **96.22\%** & **89.23\%** & **0.00\%** \\ \hline \hline \end{tabular}
\end{table} 
Table 12: Class 8 test result. ### Discussion

Out of 360 test results consisting of ten datasets, three generation models, and three detection models, our algorithm achieved 354 optimal results.