TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS

TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS

Land use and land cover are two important variables in remote sensing. Commonly, the information of land use is stored in geospatial databases. In order to update such databases, we present a new approach to determine the land cover and to classify land use objects using convolutional neural network...

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Bibliographic Details
Main Authors:	C. Yang, F. Rottensteiner, C. Heipke
Format:	Article
Language:	English
Published:	Copernicus Publications 2019-06-01
Series:	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:	https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/139/2019/isprs-archives-XLII-2-W13-139-2019.pdf

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