MRENet: Simultaneous Extraction of Road Surface and Road Centerline in Complex Urban Scenes from Very High-Resolution Images

Automatic extraction of the road surface and road centerline from very high-resolution (VHR) remote sensing images has always been a challenging task in the field of feature extraction. Most existing road datasets are based on data with simple and clear backgrounds under ideal conditions, such as im...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 13; H. 2; S. 239
Hauptverfasser:	Shao, Zhenfeng, Zhou, Zifan, Huang, Xiao, Zhang, Ya
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.01.2021
Schlagworte:	Algorithms artificial intelligence Artificial neural networks Convolution convolutional neural networks Datasets Deep learning digital images Entropy (Information theory) Experiments Feature extraction geospatial data processing High resolution Image resolution Information processing Internet Machine learning multitask learning Neural networks Receptive field Remote sensing road centerline extraction Road surface road surface extraction roads Roads & highways Satellite imagery Satellites Task complexity urban areas VHR remote sensing images
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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