@InProceedings{PereiraSant:2017:ImReLe,
author = "Pereira, {\'E}rico Marco Dias Alves and dos Santos, Jefersson
Alex",
affiliation = "{Universidade Federal de Minas Gerais} and {Universidade Federal
de Minas Gerais}",
title = "Image representation learning by color quantization optimization",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "representation learning, color quantization, CBIR, genetic
algorithm, feature extraction.",
abstract = "The state-of-art methods of representation learning, based on Deep
Neural Networks, present serious drawbacks regarding usage
complexity and resources consumption, leaving space for simpler
alternatives. We proposed two approaches of a Representation
Learning method which aims to provide more effective and compact
image representations by optimizing the colour quantization for
the image domain. Our hypothesis is that changes in the
quantization affect the description quality of the features
enabling representation improvements. We evaluated the method
performing experiments for the task of Content-Based Image
Retrieval on eight known datasets. The results showed that the
first approach, focused on representation effectiveness, produced
representations that outperforms the baseline in all the tested
scenarios. And the second, focused on compactness, was able to
produce superior results maintaining or even reducing the
dimensionality and representations until 25% smaller that
presented statistically equivalent performance.",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
language = "en",
ibi = "8JMKD3MGPAW/3PJ6MCH",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PJ6MCH",
targetfile = "Pereira_DosSantos_2017.pdf",
urlaccessdate = "2024, May 02"
}