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Knowledge-driven image mining system for Big Earth Observation data fusion: GIS maps inclusion in active learning stage

Alonso, Kevin and Datcu, Mihai (2014) Knowledge-driven image mining system for Big Earth Observation data fusion: GIS maps inclusion in active learning stage. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2014, pp. 3538-3541. IEEE Xplore. IGARSS 2014, 13.-18. Juli 2014, Quebec City, Canada. DOI: 10.1109/IGARSS.2014.6947246

Full text not available from this repository.

Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6947246

Abstract

In this paper, we present an accelerated knowledge-driven content-based information mining system for Big Earth Observation data fusion. The tool combines, at pixel level, the unsupervised clustering results of different number of features. The features, extracted from different EO raster image types and from existing GIS vector maps, are combined, in form of a BoW, with a user given semantic concepts in order to calculate the posterior probability that allows the final search. The inclusion of GIS data during the active learning, based on Bayesian networks, accelerate the definition processes of semantic labels and retrieve the related images with only a few user interactions. The inclusion of GIS data in conjunction with the recently introduced search algorithm have as a result a system which greatly optimizes the computational costs and over performs existing similar systems in various orders of magnitude.

Item URL in elib:https://elib.dlr.de/94386/
Document Type:Conference or Workshop Item (Speech)
Title:Knowledge-driven image mining system for Big Earth Observation data fusion: GIS maps inclusion in active learning stage
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Alonso, Kevinkevin.alonso (at) dlr.deUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:July 2014
Journal or Publication Title:Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2014
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2014.6947246
Page Range:pp. 3538-3541
Editors:
EditorsEmail
UNSPECIFIEDIEEE
Publisher:IEEE Xplore
Status:Published
Keywords:Active Learning, Bag of Words, Bayesian Networks, Big data, Data Fusion, GIS, Image Mining
Event Title:IGARSS 2014
Event Location:Quebec City, Canada
Event Type:international Conference
Event Dates:13.-18. Juli 2014
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By:INVALID USER
Deposited On:08 Jan 2015 16:41
Last Modified:08 Jan 2015 16:41

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