Semantic Labeling of Large-Area Geographic Regions Using Multiview and Multidate Satellite Images and Noisy OSM Training Labels

Semantic Labeling of Large-Area Geographic Regions Using Multiview and Multidate Satellite Images and Noisy OSM Training Labels

We present a novel multiview training framework and convolutional neural network (CNN) architecture for combining information from multiple overlapping satellite images and noisy training labels derived from OpenStreetMap (OSM) to semantically label buildings and roads across large geographic region...

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Bibliographic Details
Main Authors: Bharath Comandur, Avinash C. Kak
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
deep learning
digital surface model (DSM)
multiview semantic segmentation
noisy labels
OpenStreetMap (OSM)
Online Access:https://ieeexplore.ieee.org/document/9380895/

Internet

https://ieeexplore.ieee.org/document/9380895/

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