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UHER, V. BURGET, R. KARÁSEK, J. MAŠEK, J. DUTTA, M.
Original Title
Automatic Image Labelling using Similarity Measures
Type
conference paper
Language
English
Original Abstract
Scene classification based on global features. It can be used, for example, for annotating large databases of photos. The whole process has several steps. The first step is features extraction, and then the distance between a new image and reference images is calculated. A model is trained to classify new images based on this distance. The model was created using the Naïve Bayes classifier. To improve accuracy the forward selection was used, which optimizes the selection of a group of attributes. The overall performance on the testing dataset was 69.76%.
Keywords
Scene classification; image labelling; machine learning; image processing
Authors
UHER, V.; BURGET, R.; KARÁSEK, J.; MAŠEK, J.; DUTTA, M.
RIV year
2014
Released
12. 1. 2015
Publisher
IEEE
Location
Greater Noida
ISBN
978-1-4799-5096-6
Book
MEDCOM 2014 CD-ROM
Pages from
101
Pages to
104
Pages count
4
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7005984&refinements%3D4273474444%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A7005558%29
BibTex
@inproceedings{BUT109408, author="Václav {Uher} and Radim {Burget} and Jan {Karásek} and Jan {Mašek} and Malay Kishore {Dutta}", title="Automatic Image Labelling using Similarity Measures", booktitle="MEDCOM 2014 CD-ROM", year="2015", pages="101--104", publisher="IEEE", address="Greater Noida", doi="10.1109/MedCom.2014.7005984", isbn="978-1-4799-5096-6", url="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7005984&refinements%3D4273474444%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A7005558%29" }