## 3 Results  
The distribution of 300 images used in the training process is displayed in Table 1. The performance of the deployed model is demonstrated in Tables 2-5. Figures 5 and 6 provide the confusion matrix, which demonstrates the actual detection throughout the test, both correct and incorrect detections. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Image Categories** & **Number of Images** \\ \hline
4.2 \(\times\) 8 & 13 \\
4.2 \(\times\) 10 & 10 \\
4.2 \(\times\) 12 & 68 \\
5.0 \(\times\) 8 & 23 \\
5.0 \(\times\) 10 & 20 \\
5.0 \(\times\) 12 & 47 \\ Int SFE & 55 \\ Lat SFE & 64 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The distribution of each image’s categories. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number of Images** & **Original Model 1 ** & **Blurred Augmented** & **Sharpened** & **Colored Augmented** & **Noise Augmented** \\
50 & 37.50\% (6/16) & 56.25\% (9/16) & 50.00\% (8/16) & 31.25\% (5/16) & 56.25\% (9/16) \\
100 & 50.00\% (8/16) & 56.25\% (9/16) & 68.75\% (11/16) & 87.50\% (14/16) & 68.75\% (11/16) \\
150 & 81.25\% (13/16) & 81.25\% (13/16) & 75.00\% (12/16) & 56.25\% (9/16) & 68.75\% (11/16) \\
200 & 62.50\% (10/16) & 62.50\% (10/16) & 87.50\% (14/16) & 75.00\% (12/16) & 75.00\% (12/16) \\
250 & 75.00\% (12/16) & 75.00\% (12/16) & 68.75\% (11/16) & 87.50\% (14/16) & 68.75\% (11/16) \\
300 & 62.50\% (10/16) & 75.00\% (12/16) & 62.50\% (10/16) & 56.25\% (9/16) & 50.00\% (8/16) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The cross-sectional detection of each model. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Images** & **Original Model 2 ** & **Blurred Augmented** & **Sharpened** & **Colored Augmented** & **Noise Augmented** \\
50 & 100\% (2/2) & 100\% (2/2) & 100\% (3/1) & 100\% (2/2) & 50.00\% (1/2) \\
100 & 83.33\% (5/6) & 83.33\% (5/6) & 66.67\% (4/6) & 85.71\% (6/7) & 83.33\% (5/6) \\
150 & 70.00\% (7/10) & 81.81\% (9/11) & 72.72\% (8/11) & 71.42\% (5/7) & 75.00\% (6/8) \\
200 & 66.67\% (6/9) & 80.00\% (8/10) & 81.81\% (9/11) & 80.00\% (8/10) & 57.14\% (4/7) \\
250 & 62.50\% (5/8) & 70.00\% (7/10) & 61.53\% (8/13) & 77.78\% (7/9) & 54.54\% (6/11) \\
300 & 60.00\% (6/10) & 41.66\% (5/12) & 71.42\% (5/7) & 100\% (5/5) & 62.50\% (5/8) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The panoramic accuracy of each model. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number of Images** & **Original Model 3 ** & **Blurred Augmented** & **Sharpened** & **Colored Augmented** & **Noise Augmented** \\
50 & 37.50\% (6/16) & 56.25\% (9/16) & 50.00\% (8/16) & 31.25\% (5/16) & 56.25\% (9/16) \\
100 & 50.00\% (8/16) & 56.25\% (9/16) & 68.75\% (11/16) & 87.50\% (14/16) & 68.75\% (11/16) \\
150 & 81.25\% (13/16) & 81.25\% (13/16) & 75.00\% (12/16) & 56.25\% (9/16) & 68.75\% (11/16) \\
200 & 62.50\% (10/16) & 62.50\% (10/16) & 87.50\% (14/16) & 75.00\% (12/16) & 75.00\% (12/16) \\
250 & 75.00\% (12/16) & 75.00\% (12/16) & 68.75\% (11/16) & 87.50\% (14/16) & 68.75\% (11/16) \\
300 & 62.50\% (10/16) & 75.00\% (12/16) & 62.50\% (10/16) & 56.25\% (9/16) & 50.00\% (8/16) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The cross-sectional detection of each model. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number of Images** & **Original Model 4 ** & **Blurred Augmented** & **Sharpened** & **Colored Augmented** & **Noise Augmented** \\
50 & 100\% (2/2) & 100\% (2/2) & 100\% (3/1) & 100\% (2/2) & 50.00\% (1/2) \\
100 & 83.33\% (5/6) & 83.33\% (5/6) & 66.67\% (4/6) & 85.71\% (6/7) & 83.33\% (5/6) \\
150 & 70.00\% (7/10) & 81.81\% (9/11) & 72.72\% (8/11) & 71.42\% (5/7) & 75.00\% (6/8) \\
200 & 66.67\% (6/9) & 80.00\% (8/10) & 81.81\% (9/11) & 80.00\% (8/10) & 57.14\% (4/7) \\
250 & 62.50\% (5/8) & 70.00\% (7/10) & 61.53\% (8/13) & 77.78\% (7/9) & 54.54\% (6/11) \\
300 & 60.00\% (6/10) & 41.66\% (5/12) & 71.42\% (5/7) & 100\% (5/5) & 62.50\% (5/8) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The cross-sectional accuracy of each model.