| Method | Advantage | Disadvantage |
| Alexnet | The network is simple and easy to train, and it can realize image classification. | Unable to process image semantics segmentation and multi-classification |
| VGG | The network is more complex and better accuracy than Alexnet. | Unable to process image semantics segmentation and multi-classification |
| FCN | This method can process image semantics segmentation and multi-classification | The network is complex with too many redundant parameters. And its efficiency is low. |
| SegNet | It improve the encoder-decoder model. With the structure SegNet has the same segmentation accuracy with less training parameters | Semantic segmentation accuracy depends on the design and adjustment of network structure |
| Deep Lab | It introduces the encoder-decoder architecture and adopts the Xception model. This Improvement get better accuracy | The network is complex and hard to adjust. |