Modality prediction of biomedical literature images using multimodal feature representation

Modality prediction of biomedical literature images using multimodal feature representation

This paper presents the modelling approaches performed to automatically predict the modality of images found in biomedical literature. Various state-of-the-art visual features such as Bag-of-Keypoints computed with dense SIFT descriptors, texture features and Joint Composite Descriptors were used fo...

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Bibliographic Details
Main Authors: Pelka, Obioma, Friedrich, Christoph M.
Format: Article
Language:deu
Published: German Medical Science GMS Publishing House 2016-08-01
Series:GMS Medizinische Informatik, Biometrie und Epidemiologie
Subjects:
biomedical literature
multimodal imaging
principal component analysis
Random Forest
support vector machines
Online Access:http://www.egms.de/static/en/journals/mibe/2016-12/mibe000166.shtml

Internet

http://www.egms.de/static/en/journals/mibe/2016-12/mibe000166.shtml

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