Publication: Early and Late Fusion of Classifiers fo...
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Title: | Early and Late Fusion of Classifiers for the MediaEval Medico Task |
Subtitle: | |
Abstract: | In this paper we present our results for the MediaEval 2018 Medico task, achieved with traditional machine learning methods, such as logistic regression, support vector machines, and random forests. Before classification, we combine traditional global image features and CNN-based features (early fusion), and apply soft voting for combining the output of multiple classifiers (late fusion). Linear support vector machines turn out to provide both good classification performance and low run-time complexity for this task. |
Keywords: |
Publication type: | Article in compilation (Authorship) |
Publication date: | 10.2018 (Online) |
Published by: |
Working Notes Proceedings of the MediaEval 2018 Workshop
Working Notes Proceedings of the MediaEval 2018 Workshop
(
CEUR Workshop Proceedings (CEUR-WS.org);
)
to publication |
Title of the series: | - |
Volume number: | - |
First publication: | Yes |
Version: | - |
Page: | - |
Versionen
Keine Version vorhanden |
Publication date: | 10.2018 |
ISBN (e-book): | - |
eISSN: | - |
DOI: | - |
Homepage: | http://ceur-ws.org/Vol-2283/ |
Open access |
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Authors
Mario Taschwer (internal) |
Manfred Jürgen Primus (internal) |
Klaus Schöffmann (internal) |
Oge Marques (external) |
Assignment
Organisation | Address | ||||
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Fakultät für Technische Wissenschaften
Institut für Informationstechnologie
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AT - 9020 Klagenfurt am Wörthersee |
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Research Cluster | No research Research Cluster selected |
Peer reviewed |
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Publication focus |
Classification raster of the assigned organisational units:
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working groups |
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Cooperations
Organisation | Address | ||
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Florida Atlantic University (FAU)
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US
Boca Raton |
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Publications: | No related publications |
Events: | No related events |
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