# Influence of Training Parameters on Real-Time Similar Object Detection Using YOLOv5s
## 4 Experimental Investigation
### The Results of Experiments
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Image** & **Batch Size** & **Number of** & **Correctly** & **Recognition** \\
**Resolution** & & **Iterations** & **Detected** & **Ratio** \\ \hline \multirow{8}{*}{320} & 16 & \multirow{8}{*}{100} & 22 & 0.1946 \\ \cline{2-5}  & 32 & & 2 & 0.0177 \\ \cline{2-5}  & 64 & & 0 & 0 \\ \cline{2-5}  & 128 & & 0 & 0 \\ \cline{2-5}  & 16 & & 69 & **0.6106** \\ \cline{2-5}  & 32 & & 75 & **0.6637** \\ \cline{2-5}  & 64 & & 54 & 0.4778 \\ \cline{2-5}  & 16 & & 69 & **0.6106** \\ \cline{2-5}  & 32 & & 600 & 64 & 0.5663 \\ \cline{2-5}  & 64 & & 62 & 0.5486 \\ \hline \multirow{8}{*}{640} & 16 & \multirow{8}{*}{300} & 69 & **0.6106** \\ \cline{2-5}  & 32 & & 62 & 0.5486 \\ \cline{2-5}  & 64 & & 62 & 0.5486 \\ \cline{2-5}  & 16 & & 63 & 0.5575 \\ \cline{2-5}  & 32 & & 41 & 0.3628 \\ \cline{2-5}  & 64 & & 60 & 0.5309 \\ \hline \multirow{2}{*}{1280} & \multirow{2}{*}{16} & 300 & 59 & 0.5221 \\ \cline{2-5}  & & 600 & 54 & 0.4778 \\ \hline \end{tabular}
\end{table} 
Table 1: Testing results of model trained on 117 color images of 16 classes. In Table 2, results of models trained on greyscale images has been presented. In Table 2, results of models trained on greyscale images has been presented. The same as when using the color images, the worst recognition ratio results have been obtained when the iteration number is equal to 100. Almost all models do not recognize any construction details. The best results of the recognition ratio (0.4867) are achieved when the image resolution is equal to 320, the batch size is equal to 16, and the iteration number is equal to 300. In this case, the results are significantly lower compared to models trained on color images. The results using the highest image resolution do not differ from the results of the models trained on the color images. The highest recognition ratio (0.4070) has been obtained when the \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Image Resolution** & **Batch Size** & \begin{tabular}{c} **Number of** \\ **Iterations** \\ \end{tabular} & \
\begin{tabular}{c} **Correctly** \\ **Detected** \\ \end{tabular} &
\begin{tabular}{c} **Recognition** \\ **Ratio** \\ \end{tabular} \\ \hline \multirow{8}{*}{320} & 16 & \multirow{8}{*}{100} & 6 & 0.0531 \\ \cline{2-4}  & 32 & & 0 & 0 \\ \cline{2-4}  & 64 & & 0 & 0 \\ \cline{2-4}  & 128 & & 0 & 0 \\ \cline{2-4}  & 16 & & 55 & 0.4867 \\ \cline{2-4}  & 32 & & 38 & 0.3362 \\ \cline{2-4}  & 64 & & 40 & 0.3539 \\ \cline{2-4}  & 16 & & 47 & 0.4159 \\ \cline{2-4}  & 32 & & 49 & 0.4336 \\ \cline{2-4}  & 64 & & 50 & 0.4424 \\ \hline \multirow{8}{*}{640} & 16 & \multirow{8}{*}{600} & 48 & 0.4247 \\ \cline{2-4}  & 32 & & 51 & 0.4513 \\ \cline{2-4}  & 64 & & **65** & **0.5752** \\ \cline{2-4}  & 16 & & 52 & 0.4601 \\ \cline{2-4}  & 32 & & 45 & 0.3982 \\ \cline{2-4}  & 64 & & 41 & 0.3628 \\ \hline \multirow{2}{*}{1280} & \multirow{2}{*}{16} & 300 & 41 & 0.3628 \\ \cline{2-4}  & & & 600 & 46 & 0.4070 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Testing results of model trained on 117 greyscale images of 16 classes. Figure 7: Accuracy results of model trained on 117 greyscale images of 16 classes. batch size is equal to 16 and the iteration number is equal to 600. Of all trained models that used greyscale images, the highest recognition ratio (0.5752) was obtained when the image resolution was equal to 640, the batch size was equal to 64, and the iteration number is equal to 300. To conclude the primary research results, the parameters of four models (with highest accuracy) that obtain the highest recognition ratio have been selected for a deeper analysis (cells highlighted in orange and green in Tables 1 and 2). The four new models have been trained using the full dataset, 355 color images of 36 classes. The accuracy results of the model are presented in Figure 8. As we can see, the accuracy becomes slightly higher compared to the results of the primary research, even though the number of classes increased.