RBFNet: A Region-Aware and Boundary-Enhanced Fusion Network for Road Extraction From High-Resolution Remote Sensing Data

Most existing road extraction methods prioritize region accuracy at the expense of ignoring road boundaries and connectivity quality. The occluding objects such as buildings, trees, and vehicles in remote sensing data usually cause discontinuous mask outputs, and consequently affect road extraction...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2024, Vol.17, p.16608-16624
Hauptverfasser:	Li, Weiming, Lan, Tian, Fan, Shuaishuai, Jiang, Yonghua
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Balances (scales) Benchmarks Boundary enhancement Data mining Feature extraction Graph theory High resolution integrated GCN Masks Neural networks Object recognition parameter filtering region-aware Remote sensing road extraction Roads Semantics Transformers
Online-Zugang:	Volltext
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