Detail publikace

Automatic Image Labelling using Similarity Measures

UHER, V. BURGET, R. KARÁSEK, J. MAŠEK, J. DUTTA, M.

Originální název

Automatic Image Labelling using Similarity Measures

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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%.

Klíčová slova

Scene classification; image labelling; machine learning; image processing

Autoři

UHER, V.; BURGET, R.; KARÁSEK, J.; MAŠEK, J.; DUTTA, M.

Rok RIV

2014

Vydáno

12. 1. 2015

Nakladatel

IEEE

Místo

Greater Noida

ISBN

978-1-4799-5096-6

Kniha

MEDCOM 2014 CD-ROM

Strany od

101

Strany do

104

Strany počet

4

URL

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"
}