Land Use Classification of the Deep Convolutional Neural Network Method Reducing the Loss of Spatial Features

Land Use Classification of the Deep Convolutional Neural Network Method Reducing the Loss of Spatial Features

Land use classification is a fundamental task of information extraction from remote sensing imagery. Semantic segmentation based on deep convolutional neural networks (DCNNs) has shown outstanding performance in this task. However, these methods are still affected by the loss of spatial features. In...

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Bibliographic Details
Main Authors: Xuedong Yao, Hui Yang, Yanlan Wu, Penghai Wu, Biao Wang, Xinxin Zhou, Shuai Wang
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Sensors
Subjects:
remote sensing
semantic segmentation
DCNNs
coordconv
ISPRS
high resolution
Online Access:https://www.mdpi.com/1424-8220/19/12/2792

Internet

https://www.mdpi.com/1424-8220/19/12/2792

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