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Visualization-based Active Learning for the Annotation of SAR images

Babaee, Mohammadreza and Tsoukalas, Stefanos and Rigoll, Gerhard and Datcu, Mihai (2015) Visualization-based Active Learning for the Annotation of SAR images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8 (10), pp. 4687-4698. IEEE - Institute of Electrical and Electronics Engineers. DOI: 101109/JSTARS.2015.2388469 ISSN 1939-1404

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7018915

Abstract

Active learning has gained a high amount of attention due to its ability to label a vast amount of unlabeled collected earth observation (EO) data. In this paper, we propose a novel active learning algorithm which is mainly based on employing a low-rank classifier as the training model and introducing a visualization support data point selection, namely, first certain wrong labeled (FCWL). The training model is composed of the logistic regression loss function and the trace-norm of learning parameters as regularizer. FCWL selects those data points whose labels are predicted wrong but the classifier is highly certain about them. Our experimental results performed on different extracted features from a dataset of SAR images confirm at least 10% improvement over the state-of-the-art methods.

Item URL in elib:https://elib.dlr.de/100111/
Document Type:Article
Title:Visualization-based Active Learning for the Annotation of SAR images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Babaee, MohammadrezaTechnical University Munich, GermanyUNSPECIFIED
Tsoukalas, StefanosTechnical University Munich, GermanyUNSPECIFIED
Rigoll, GerhardTechnical University Munich, GermanyUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:October 2015
Journal or Publication Title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:8
DOI :101109/JSTARS.2015.2388469
Page Range:pp. 4687-4698
Editors:
EditorsEmail
Chanussot, Jocelynjocelyn.chanussot@gipsa-lab.grenoble-inp.fr
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:Published
Keywords:Active learning, synthetic aperture radar (SAR), trace-norm regularized classifier, visualization
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: Schwarz, Gottfried
Deposited On:30 Nov 2015 10:37
Last Modified:08 Mar 2018 18:32

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