Road Extraction from Remote Sensing Imagery with Spatial Attention Based on Swin Transformer

• Published in: Remote sensing (Basel, Switzerland) Vol. 16; no. 7; p. 1183
• Main Authors: Zhu, Xianhong, Huang, Xiaohui, Cao, Weijia, Yang, Xiaofei, Zhou, Yunfei, Wang, Shaokai
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Algorithms; China; Complexity; Computational linguistics; data collection; Datasets; Deep learning; Feature maps; Global positioning systems; GPS; Image processing; Imagery; Language processing; Massachusetts; Methods; Modules; Natural language interfaces; Neural networks; Occlusion; Performance evaluation; Remote sensing; remote sensing applications; road extraction; Roads; Roads & highways; Semantics; Spatial data; Spatial MLP; spatial self-attention; Streets; traffic; Urban planning; China; Massachusetts

Road extraction is a crucial aspect of remote sensing imagery processing that plays a significant role in various remote sensing applications, including automatic driving, urban planning, and path navigation. However, accurate road extraction is a challenging task due to factors such as high road de...