## 3 Results and Discussion
### Observation of Bubbles Detection and \(H_{2}\) Evolution
The IoU, on the other hand, is an indicator that quantifies the extent of the overlap between the bounding box predicted by the object detection model and the actual object. This value is obtained by dividing the overlapped region of the two bounding boxes by the total area covered by the bounding boxes in the image. In the context of mAP, the term \"mAP\" stands for mean average precision. AP represents the area under the precision-recall graph. Specifically, mAP is the average value obtained by summing the AP values for each class and dividing it by the total number of classes. A value is usually appended after the mAP to signify the threshold used to determine the reliability of the bounding box when calculating the mAP. The values were recorded at regular intervals, typically every 1000 iterations, during the training process. As depicted in Figure 9a,b, the training has been conducted effectively by reaching a point where the loss has significantly reduced, the accuracy has plateaued, and further improvements are minimal. Table 4 presents a detailed overview of the test results based on the mAP of the dataset. The mAP in YOLOv4 serves as an indicator of the bounding box accuracy, which can vary when the model is exposed to new environments or scenarios involving bubbles. However, due to the supervised learning approach employed, the model may struggle to recognize unfamiliar objects [59]. Figure 10 shows that there are a few bubbles that the model fails to identify, and there is a noticeable distinction between the right and left sides of the metal surface. The darker appearance on the right side indicates greater corrosion (after the corrosion process) compared to the relatively less-corroded left side. The number of bubbles detected in the PP test is given in Table 5. The SM exhibited distinct effects in the WM, HAZ, and BM zones. Subsequently, this count was further divided according to the specific welding areas, namely, the WM, HAZ, and BM. By dividing the number of bubbles detected by the respective area of each welding zone, the ratio between the bubble count and the area for each specific welding area at a given time is obtained. The measured volume of the H2 gas (Figure 2b) that evolved during the PP test (from 0 to 10 min) is given in Table 6. The SM demonstrated a different effect on the weld metal (WM) zone and heat-affected zone (HAZ)-base metal (BM) zone. Figure 11 shows the comparison between the hydrogen rate and corrosion rate of the specimens tested with different concentrations of SM. The graph shows a similar trend for the H2 evolution rate and corrosion rate. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **mAP** & **Average IoU** & **Precision** & **Recall** & **F1-Score** \\ \hline [EMAIL_ADDRESS] & 97.11\% & 60.23\% & 0.77 & 0.98 & 0.86 \\ [EMAIL_ADDRESS] & 50.48\% & 43.34\% & 0.53 & 0.66 & 0.59 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Detailed testing results. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Inhibitor Concentration (g/L)** & **WM** & **HAZ** & **BM** \\ \hline
0 & 2.411\(\pm\) 0.121 & 2.950 \(\pm\) 0.148 & 2.025 \(\pm\) 0.101 \\ \hline
0.1 & 1.032 \(\pm\) 0.052 & 1.314 \(\pm\) 0.065 & 1.252 \(\pm\) 0.062 \\ \hline
0.2 & 0.652 \(\pm\)