On the Fusion of Text Detection Results: A Genetic Programming Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @Article{Flores-Campana:2020:ACC,
-
author = "Jose L. {Flores Campana} and Allan Pinto and
Manuel Alberto {Cordova Neira} and
Luis Gustavo {Lorgus Decker} and Andreza Santos and
Jhonatas S. Conceicao and Ricardo {Da Silva Torres}",
-
journal = "IEEE Access",
-
title = "On the Fusion of Text Detection Results: A Genetic
Programming Approach",
-
year = "2020",
-
volume = "8",
-
pages = "81257--81270",
-
keywords = "genetic algorithms, genetic programming, Scene text
detection, multi-oriented text, convolutional neural
network, data fusion",
-
DOI = "doi:10.1109/ACCESS.2020.2987869",
-
ISSN = "2169-3536",
-
size = "14 pages",
-
abstract = "Hundreds of text detection methods have been proposed,
motivated by their widespread use in several
applications. Despite the huge progress in the area,
which includes even the use of sophisticated learning
schemes, ad-hoc post-processing procedures are often
employed to improve the text detection rate, by
removing both false positives and negatives. Another
issue refers to the lack of the use of the
complementary views provided by different text
detection methods. This paper aims to fill these gaps.
We propose the use of a soft computing framework, based
on genetic programming (GP), to guide the definition of
suitable post-processing procedures through the
combination of basic operators, which may be applied to
improve detection results provided by multiple methods
at the same time. Performed experiments in the widely
used ICDAR 2011, ICDAR 2013, and ICDAR 2015 datasets
demonstrate that our GP-based approach leads to F1
effectiveness gains up to 5.1 percentage points, when
compared to several baselines.",
-
notes = "Also known as \cite{9066990}",
- }
Genetic Programming entries for
Jose L Flores Campana
Allan Pinto
Manuel Alberto Cordova Neira
Luis Gustavo Lorgus Decker
Andreza Aparecida dos Santos
Jhonatas S Conceicao
Ricardo da Silva Torres
Citations