# Image Semantic Segmentation Fusion of Edge Detection and AFF Attention Mechanism
## 5 Conclusions  
Deep learning has been widely used in the field of image understanding. With the development of deep learning, the accuracy of image semantic segmentation has also been greatly improved. In this paper, we proposed a hybrid semantic segmentation model, which combines the improved HED network with the improved PSP-Net, and adds the AFF attention mechanism. In the improved PSP-Net network, we use the MobileNetv3 network to instead be the encoder of the original PSP-Net network. In the improved HED network, the last full link in the HED network is removed to obtain a complete convolutional network, and extended convolution is introduced to increase the acceptance domain of feature extraction. The improved HED network can effectively extract features at different scales, and learn features at other scales while doing so. The AFF attention mechanism can improve the response recognition ability for specific scenes and enhance  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Name** & **DeepLabV3+** & **PSP-Net** & **Our Proposed Model** \\ \hline
**Average** & 80.15 & 81.23 & 83.38 \\ Road & 97.52 & 94.45 & 97.21 \\ Sidewalk & 82.73 & 81.69 & 86.32 \\ Building & 92.25 & 91.12 & 80.56 \\ Wall & 51.21 & 50.61 & 82.45 \\ Fence & 53.64 & 50.83 & 80.26 \\ Pole & 58.27 & 57.52 & 81.38 \\ Traffic light & 61.19 & 60.93 & 73.92 \\ Traffic sign & 70.46 & 68.34 & 92.64 \\ Vegetation & 90.52 & 90.15 & 63.11 \\ Terrain & 62.21 & 61.87 & 94.17 \\ Sky & 95.73 & 93.67 & 75.67 \\ ocean & 94.62 & 89.79 & 76.82 \\ Person & 72.95 & 70.11 & 80.76 \\ Rider & 60.34 & 58.29 & 93.82 \\ Car & 94.58 & 93.12 & 61.93 \\ Truck & 63.72 & 61.24 & 75.98 \\ Bus & 78.16 & 73.35 & 54.86 \\ Train & 53.64 & 53.57 & 55.24 \\ Motorcycle & 52.72 & 50.61 & 52.35 \\ Bicycle & 71.91 & 69.48 & 83.21 \\ \hline \hline \end{tabular}
\end{table}
Table 7: MIOU.  
the segmentation accuracy of small target objects. There are four places where the AFF attention mechanism can be inserted. In order to achieve the best segmentation effect, we carried out experiments on four positions, respectively. The experimental results show that adding AFF to the feature fusion part of the improved PSP-Net and the improved HED network can obtain the best effect. This hybrid model has experimented on the Cityscapes dataset and the SIFT Flow dataset. The experimental results prove that the model can not only improve the segmentation accuracy of complex scene images and small objects, but also improve the convergence speed and fitting degree of the model when training images in complex scenes.  
Conceptualization, X.W. and W.W.; formal analysis, X.W.; investigation, W.W.; resources, X.W.; data curation, Y.J.; writing--original draft preparation, Y.J.; writing--review and editing, S.L. All authors have read and agreed to the published version of the manuscript.  
Not applicable.  
Experiment data can obtain at [[https://github.com/jiaoyjie/data-for-semantic-segmentation](https://github.com/jiaoyjie/data-for-semantic-segmentation)]([https://github.com/jiaoyjie/data-for-semantic-segmentation](https://github.com/jiaoyjie/data-for-semantic-segmentation)).  
The authors declare no conflict of interest.