A locally-constrained YOLO framework for detecting small and densely-distributed building footprints

Building footprints are among the most predominant features in urban areas, and provide valuable information for urban planning, solar energy suitability analysis, etc. We aim to automatically and rapidly identify building footprints by leveraging deep learning techniques and the increased availabil...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	International journal of geographical information science : IJGIS 2020-04, Vol.34 (4), p.777-801
Hauptverfasser:	Xie, Yiqun, Cai, Jiannan, Bhojwani, Rahul, Shekhar, Shashi, Knight, Joseph
Format:	Artikel
Sprache:	eng
Schlagworte:	Building detection Datasets Deep learning Footprints locally constrained Machine learning Object recognition Regression analysis Remote sensing Robustness (mathematics) Solar energy Spatial resolution Urban areas Urban planning YOLO
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!