Road Extraction of High-Resolution Remote Sensing Images Derived from DenseUNet

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 21; p. 2499
• Main Authors: Xin, Jiang, Zhang, Xinchang, Zhang, Zhiqiang, Fang, Wu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.10.2019
• Subjects: Algorithms; artificial intelligence; Automation; buildings; Computer applications; data collection; denseunet; Disaster management; Emergency preparedness; Emergency response; Emergency vehicles; High resolution; high-resolution remote sensing imagery; Image resolution; Image segmentation; Intelligent transportation systems; Learning algorithms; Machine learning; Methods; multi-scale; Neural networks; Parameter robustness; Remote sensing; road extraction; roads; Roads & highways; Semantics; Skips; Transportation networks; Urban areas

Road network extraction is one of the significant assignments for disaster emergency response, intelligent transportation systems, and real-time updating road network. Road extraction base on high-resolution remote sensing images has become a hot topic. Presently, most of the researches are based on...