Road extraction from satellite and aerial image using SE-Unet

Road extraction as a significant role in traffic management, road monitoring, and autodriving cars have been important research topics in recent years. A deep learning method based on U-net and spatially squeeze and exciting channelwise (SE) is proposed for recognizing road. The SE attention block reweights feature maps from U-net layers and highlights only useful channels. We added this block to U-net and test out proposed method on two road datasets. Finally, we compare our method with other methods, and the results demonstrate that the proposed method outperforms other networks. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

Automated summary

Road extraction, an important research topic in the fields of traffic management, road monitoring, and autonomous driving cars, has been addressed using a deep learning method based on U-net and SE. The method effectively recognizes roads and outperforms other networks in testing on two road datasets.