Amanote Research
Register
Sign In
Building Footprint Extraction From Digital Surface Models Using Neural Networks
doi 10.1117/12.2240727
Full Text
Open PDF
Abstract
Available in
full text
Date
October 18, 2016
Authors
Ksenia Davydova
Shiyong Cui
Peter Reinartz
Publisher
SPIE
Related search
Building Footprint Extraction From VHR Remote Sensing Images Combined With Normalized DSMs Using Fused Fully Convolutional Networks
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Atmospheric Science
Computers in Earth Sciences
Robust Building Footprint Extraction From Big Multi-Sensor Data Using Deep Competition Network
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Automatic Extraction and Building Change Detection From Digital Surface Model and Multispectral Orthophoto
Geodetski Vestnik
Earth
Planetary Sciences
Using Convolutional Neural Networks for Sentiment Attitude Extraction From Analytical Texts
Comparison of Digital Building Height Models Extracted From AW3D, TanDEM-X, ASTER, and SRTM Digital Surface Models Over Yangon City
Remote Sensing
Earth
Planetary Sciences
Extracting Polygonal Building Footprints From Digital Surface Models: A Fully-Automatic Global Optimization Framework
ISPRS Journal of Photogrammetry and Remote Sensing
Development
Computers in Earth Sciences
Molecular Physics,
Planning
Engineering
Computer Science Applications
Atomic
Optics
Geography
Prediction of Surface Distress Using Neural Networks
Building Extraction From Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network
Remote Sensing
Earth
Planetary Sciences
Urban Object Extraction From Digital Surface Model and Digital Aerial Images
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Instrumentation
Earth
Planetary Sciences
Environmental Science
