# PBA-YOLOv7: An Object Detection Method Based on an Improved YOLOv7 Network
## 3 Experimental Results and Analysis
### Ablation Experiment and Analysis  
To verify the improvement effect of the algorithm in this paper, ablation experiments are used to verify each improved scheme under the condition that the environment and parameter settings are kept uniform. Improvement point ablation experiments are carried out in seven groups, with YOLOv7 as the baseline model, \"\(\surd\)\" indicates that the corresponding improvement point is selected, and each improvement point is first added to \begin{table}
\begin{tabular}{c c c} \hline \hline
**Model** & **[EMAIL_ADDRESS]** & **FPS** \\ \hline SSD & 44.03\% & 39 \\ Faster R-CNN & 55.2\% & 17 \\ YOLOv5I & 87.4\% & 40 \\ YOLOv7-tiny & 85.3\% & 48 \\ YOLOv7 & 90.5\% & 37 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of object detection algorithms. the original model of YOLOv7 individually and sequentially to carry out the ablation experiments. Model 6 is the model of this paper's algorithm (PFA-YOLOv7) and the results of the experiments are shown in Table 4. The comparison diagram of the model of the ablation experiments is shown in Figure 7.  
The following conclusions can be drawn from Table 4:  
1. Model 1 results from the original YOLOv7 algorithm experiment, a comparison benchmark for the following sets of experiments. Its parameter count is 37,208 K, model size is 74.8 M, mean average precision [EMAIL_ADDRESS] is 90.5%, [EMAIL_ADDRESS] is 60.5%, frames precision second (FPS) is 37. 2. Model 2 is the ELAN module that introduces a partial convolution to improve the backbone network based on model 1, which not only reduces the number of parameters and the size of the model relative to model 1, but also improves the mean average precision and frames precision second based on this model. 3. Model 3 is based on model 1, wherein only the BiFusionNet module is replaced, and this model keeps the number of parameters unchanged, based on which the mean average precision and frames precision second is substantially improved. 4. Model 4 is based on model 1 and introduces the coordinate attention mechanism. This model improves the mean average precision while reducing the frame's precision by a second. 5. Model 5 is based on model 1, which sequentially introduces the ELAN module for partial convolutional improvement of the backbone network and introduces the BiFusionNet module in the enhanced feature extraction network. This model \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Model** & **YOLOv7** & **PConv** & **BiFusionNet** & **CA** & **Parameters** & **Size** & **[EMAIL_ADDRESS]** & **[EMAIL_ADDRESS]** & **FPS** \\ \hline
1 & \(\surd\) & & & & 37,208 K & 74.8 M & 90.5\% & 60.5\% & 37 \\
2 & \(\surd\) & \(\surd\) & & & 32,699 K & 66.5 M & 91.8\% & 62.4\% & 45 \\
3 & \(\surd\) & & \(\surd\) & & 37,113 K & 73.6 M & 92.8\% & 65.3\% & 41 \\
4 & \(\surd\) & & & \(\surd\) & 32,253 K & 75.2 M & 94.4\% & 69.1\% & 32 \\
5 & \(\surd\) & \(\surd\) & \(\surd\) & & 32,604 K & 65.5 M & 92.0\% & 63.4\% & 47 \\
6 & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & 32,640 K & 65.7 M & 94.5\% & 68.3\% & 43 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Improved point ablation experiment. Figure 7: Comparison of experimental data of improved point ablation [EMAIL_ADDRESS]. improves the evaluation indexes relative to Model 1 and Model 2 and improves the frame's precision second relative to Model 3 while reducing the number and size of the parameters of the model to ensure that the mean average precision does not decrease significantly. 6. Model 6 is the algorithm of this paper, which introduces the ELAN module of the partially convolutional improved backbone network, BiFusionNet module, and coordinate attention mechanism for the enhanced feature extraction network which is based on model 1. Relative to model 1, the parameter of parameters is reduced by 4568 K, the size of the model is reduced by 9.1 M, the [EMAIL_ADDRESS] is significantly improved by 4%, the [EMAIL_ADDRESS]:0.95 is significantly improved by 7.8%, and six frames significantly increase the FPS.