Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR) data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the...

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Bibliographic Details
Main Authors: Hasan Asy’ari Arief, Geir-Harald Strand, Håvard Tveite, Ulf Geir Indahl
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Remote Sensing
Subjects:
land cover segmentation
stochastic depth atrous network
IoU loss function
airborne LiDAR data
deep learning data fusion
Online Access:http://www.mdpi.com/2072-4292/10/6/973

Internet

http://www.mdpi.com/2072-4292/10/6/973

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