# _Applied sciences_
## 4 Experimental Evaluation
### Ablation Experiments  
Residual blocks in different quantities and with different structures, added to different positions of the U-Net framework, will produce different output effects. In order to explore the effect of the number of residual blocks and the advantage of the improved residual blocks, the ablation experiment shown in Figure 13 is set up to add two different structures of residual blocks (basic residual blocks and improved residual blocks) to the I, II, III, IV, and V positions of the U-Net framework, and to explore the UR-Net network structure that is the most suitable for the color images as the semantic segmentation model. Since the constructed U-Net framework is left-right symmetric, the added positions are also left-right symmetric. \begin{table}
\begin{tabular}{l l l l} \hline \multirow{2}{*}{**Confusion Matrix**} & \multicolumn{2}{c}{**Actual Class**} \\ \cline{3-4}  & & **Label** & **Background** \\ \hline \multirow{2}{*}{**Predicted class**} & **label** & True Positives (TP) & False Positives (FP) \\  & **Background** & False Negatives (FN) & True Negatives (TN) \\ \hline \end{tabular}
\end{table} 
Table 2: Confusion matrix. The adding positions of the residual blocks are set as follows:  
Add two basic residual blocks to position I of the U-Net framework, denoted as UR-Net-2b. Add two improved residual blocks to position I of the U-Net framework, denoted as UR-Net-2i. Add four basic residual blocks to positions I and II of the U-Net framework, denoted as UR-Net-4b. Add four improved residual blocks to positions I and II of the U-Net framework, denoted as UR-Net-4i. Add six basic residual blocks to positions I, II, and III of the U-Net framework, denoted as UR-Net-6b. Add six improved residual blocks to positions I, II, and III of the U-Net framework, denoted as UR-Net-6i. Add eight basic residual blocks to positions I, II, III, and IV of the U-Net framework, denoted as UR-Net-8b. Add eight improved residual blocks to positions I, II, III, and IV of the U-Net framework, denoted as UR-Net-8i. Add 10 basic residual blocks to positions I, II, III, IV, and V of the U-Net framework, denoted as UR-Net-10b. Add 10 improved residual blocks to positions I, II, III, IV, and V of the U-Net framework, denoted as UR-Net-10i. The two types of residual blocks are added in different numbers to different positions in the network structure, as shown in Table 3; \"\(\surd\)\" indicates the selected positions and numbers in the network structure. Each UR-Net with a different number of residual blocks was trained according to the set training methods and parameters, and the network structure with the highest accuracy was selected to be used as UR-Net. IoU and other data were calculated using Equations (5)-(9) to validate the usefulness of the 10 UR-Net structures, and the results are shown in Table 4. The calculation results show that the IoU and other data of UR-Net-10i are  
Figure 13: UR-Net structure setup. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Basic**} & \multirow{2}{*}{**Improved**} & \multirow{2}{*}{**Number**} & \multicolumn{6}{c}{**Positions**} \\ \cline{3-8}  & & & **I** & **II** & **III** & **IV** & **V** \\ \hline UR-Net-2b & UR-Net-2i & 2 & \(\surd\) & & & & \\ UR-Net-4b & UR-Net-4i & 4 & \(\surd\) & \(\surd\) & & & \\ UR-Net-6b & UR-Net-6i & 6 & \(\surd\) & \(\surd\) & \(\surd\) & & \\ UR-Net-8b & UR-Net-8i & 8 & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \\ UR-Net-10b & UR-Net-10i & 10 & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Positions of basic and improved residual blocks. higher than the other model structures, i.e., the maximum accuracy can be achieved when 10 improved residual blocks are added to the U-Net structure. The semantic segmentation of earth-red pixels using the model shown in Figure 14 still produces salt-and-pepper noise, which further verifies the advantage of the improved residual blocks.