Publication detail
TESTING RCE NEURAL NETWORK FOR SKIN IMAGE SEGMENTATION
HYNČICA, T.
Original Title
TESTING RCE NEURAL NETWORK FOR SKIN IMAGE SEGMENTATION
English Title
TESTING RCE NEURAL NETWORK FOR SKIN IMAGE SEGMENTATION
Type
conference paper
Language
en
Original Abstract
This paper describes my work with testing usability of a reduced Coulomb energy (RCE) neural network for skin segmentation task. Skin segmentation is an important task in computer vision. I describe three color spaces we used for skin segmentation (RGB, HSL and YCbCr). Also I briefly describe the RCE neural network. The segmentation results are described in the final section.
English abstract
This paper describes my work with testing usability of a reduced Coulomb energy (RCE) neural network for skin segmentation task. Skin segmentation is an important task in computer vision. I describe three color spaces we used for skin segmentation (RGB, HSL and YCbCr). Also I briefly describe the RCE neural network. The segmentation results are described in the final section.
Keywords
RCE neural network, color spaces, skin segmentation
RIV year
2012
Released
26.04.2012
Publisher
LITERA Brno
Location
Brno
ISBN
978-80-214-4462-1
Book
Proceedings of the 18th Conference STUDENT EEICT 2012 Volume 3
Edition number
první
Pages from
111
Pages to
115
Pages count
5
Documents
BibTex
@inproceedings{BUT91579,
author="Tomáš {Hynčica}",
title="TESTING RCE NEURAL NETWORK FOR SKIN IMAGE SEGMENTATION",
annote="This paper describes my work with testing usability of a reduced Coulomb energy (RCE) neural network for skin segmentation task. Skin segmentation is an important task in computer vision. I describe three color spaces we used for skin segmentation (RGB, HSL and YCbCr). Also I briefly describe the RCE neural network. The segmentation results are described in the final section.",
address="LITERA Brno",
booktitle="Proceedings of the 18th Conference STUDENT EEICT 2012 Volume 3",
chapter="91579",
howpublished="print",
institution="LITERA Brno",
year="2012",
month="april",
pages="111--115",
publisher="LITERA Brno",
type="conference paper"
}