## 3 Experimental Results and Analysis
### Experimental Result and Comparative Analysis
#### 3.4.2 Ablation Experiments  
To rigorously assess the impact of our proposed module on model performance, we conducted a series of ablation experiments. In order to verify the effectiveness of each module we used, we selected the YOLOV8 model with the best effect in the comparative experiment as a benchmark and compared each improved module with the unimproved YOLOV8. The experimental results are shown in Table 3, where \"-\" represents the original structure of YOLOV8, and \"+\" represents the module used in this paper.  
Group A: YOLOV8 was used for detection, and the model _mAP_50 was 0.9686;  
Group B1: Using the RevCol network to replace the backbone network of YOLOV8, the _mAP_50 value is 0.9712;  
Group C1: Replacing the C2f structure of YOLOV8 with the C2D structure, the _mAP_50 value is 0.9702;  
Group D1: Replacing the detection head of YOLOV8 with the detection head designed in this article, the _mAP_50 value is 0.9692;  
Group E1: Replacing the bounding box loss function of YOLOV8 with the MPDIoU loss function, the _mAP_50 value is 0.9689.  
In order to verify the overall detection effect of the module we designed, after we gradually added the improved structure to the design model, the _mAP_50 value of the model increased, which proved the effectiveness of the model we designed for the transmission tower line foreign matter dataset. In these experiments, we divided the proposed algorithm structure into five distinct groups for systematic comparative analysis. The experimental results are shown in Table 4, where \"-\" means that the module does not exist, and \"+\" means that the module is included.  
Group A: YOLOV8 was used for detection, and the model _mAP_50 was 0.9686;  
Group B2: Using the RevCol network to replace the backbone network of YOLOV8, the _mAP_50 value is 0.9712;  
Group C2: Replacing the C2f structure of YOLOV8 with the C2D structure based on the structure of Group B2, the _mAP_50 value is 0.9755;  
Group D2: Based on the structure of Group C2, the detection head was replaced with a decoupled detection head, and an auxiliary training head was added for training. The _mAP_50 value was 0.9785;  
Ours model: Based on group D2 experiments, the bounding box loss function is replaced with MPDIoU loss function, and the _mAP_50 value is 0.9798.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**YOLOV8** & **+RevCol** & **+C2D** & **+Detection Head** & **+MPDIoU** & _mAP_50** & **Group** \\ \hline + & - & - & - & - & 0.9686 & A \\ + & + & - & - & - & 0.9712 & B2 \\ + & + & + & - & - & 0.9755 & C2 \\ + & + & + & + & - & 0.9785 & D2 \\ + & + & + & + & + & 0.9798 & Ours model \\ \hline \hline \end{tabular}
\end{table}
Table 4: Improve results step by step.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**YOLOV8** & **+RevCol** & **+C2D** & **+Detection Head** & **+MPDIoU** & _mAP_50** & **Group** \\ \hline + & - & - & - & - & 0.9686 & A \\ + & + & - & - & - & 0.9712 & B1 \\ + & - & + & - & - & 0.9702 & C1 \\ + & - & - & + & - & 0.9692 & D1 \\ + & - & - & - & + & 0.9689 & E1 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Single improvement comparison result.