Creativision Posters and Technical Reports
creativisionPosters.bib
@comment{{This file has been generated by bib2bib 1.95}}
@comment{{Command line: /usr/bin/bib2bib -ob creativisionPosters.bib -c '$type="POSTER" or $type="TECHREPORT"' creativision.bib}}
@poster{Zanaetal2004a,
author = {Y. Zana and R. M. Cesar-Jr.},
title = {Face identification and verification using polar frequency components},
howpublished = {Poster session},
note = {Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI)},
year = {2004},
month = {17--20},
keywords = {perception, biometrics},
abstract = {We present a novel face recognition method based
on global polar frequency features. The algorithm uses Fourier-Bessel
transformation for polar frequency components extraction, conversion to a
dissimilarity space, and a Linear Discriminant classifier. Although the
algorithm performance was below that of state-of the-art methods w.r.t.
recognition rate tests, it was equivalent on verification tests. These
results indicate that recognition rates can be improved by considering more
sophisticated decision rules based on confidence levels. {\bf - This is the
author's version of the work. Not for redistribution.}},
comment = {Curitiba/PR},
keywords = {perception, biometrics},
pdf = {pdf/ZanaCesar2004a.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Face identification and verification using polar frequency components},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Face identification and verification using polar frequency components},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Face identification and verification using polar frequency components},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Face identification and verification using polar frequency components}
}
@poster{Zanaetal2004b,
author = {Y. Zana and R. M. Cesar-Jr.},
title = {Proximity relations in a polar Frequency face representation},
year = {2004},
month = {17--20 Oct.},
howpublished = {Poster session},
note = {Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI)},
keywords = {perception, biometrics},
abstract = {We assessed the representation space created by
a Fourier-Bessel transformation (FBT) of face images that varied in view
angle, translation, rotation, and scale. Multidimensional scaling analysis,
detection and recognition tests were explored to assess the conservation of
real-world proximity relations. View angle variation was well represented by
FBT raw coefficients, but not their moduli. Translation, rotation, and scale
variations were represented in a way that partially conserved the proximity
relations. These properties corroborate our representation approach. {\bf -
This is the author's version of the work. Not for redistribution.}},
conferencelocation = {Curitiba/PR},
pdf = {pdf/ZanaCesar2004b.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Proximity relations in a polar Frequency face representation},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Proximity relations in a polar Frequency face representation},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Proximity relations in a polar Frequency face representation},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Proximity relations in a polar Frequency face representation}
}
@poster{MenaChalco04a,
author = {J. P. Mena-Chalco and H. S. Alves and H. Carrer and R. M. Cesar-Jr.},
title = {Bioinformatics Tools for Assembling and Analysis of Chloroplast Genomes},
howpublished = {Poster session},
note = {International Conference on Bioinformatics and Computational Biology (ICOBICOBI)},
year = {2004},
month = {Oct.},
abstract = {Chloroplasts are organelles found only in plant and algae cells. They are responsible for photosynthesis and
for the synthesis of key molecules required for the basic architeture and functioning of plant cells. These
organelles have their own genetic machinery and together with the nucleus and mitochondrial genomes are
responsible for celular coordenation activity. At the moment 29 higher plant plastid genomes (plastomes)
have been sequenced (http://ncbi.nlm.nih.gov/). The plastome sequences are conserved among species but the
genes arrangements are different for divergent plant groups. The knowledge of the nucleotide sequence of
chloroplast genomes is important for evolution studies and for biotechnology applications. The chloroplast
organelle being used as a model in this study was isolated from Eucalyptus grandis, an important economical
tree for the production of paper and cellulose and in Brazil is located the main germoplasm collection of
Eucalyptus outside Australia.
We have sequenced 3500 sequences from an Eucalyptus DNA library. These sequences represent so
far, 50\% of the total plastome sequence of Eucalyptus grandis. These sequences are stored through a special
pipeline at the bioinformatics servers at URL http://malariadb.ime.usp.br:8026/pipeline/. Once this phase is
accomplished, the next step is the search for similar sequences in other related organisms. Some tentative
results towards this direction have been already obtained.
In this study, we apply digital signal processing (DSP) techniques on the genomic data
sequences in order to identify and compare DNA and protein sequences of Eucalyptus grandis to the other
available higher plant plastomes. We have chosen different approaches to identify protein coding DNA
regions and to compare protein sequences. In particular, traditional Fourier analysis and the wavelet transform
will be evaluated.
{\bf - This is the author's version of the work. Not for redistribution.}},
comment = {Angra dos Reis/RJ},
pdf = {pdf/MenaChalco04a.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Bioinformatics Tools for Assembling and Analysis of Chloroplast Genomes},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Bioinformatics Tools for Assembling and Analysis of Chloroplast Genomes},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Bioinformatics Tools for Assembling and Analysis of Chloroplast Genomes},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Bioinformatics Tools for Assembling and Analysis of Chloroplast Genomes}
}
@poster{MenaChalco05a,
author = {J. P. Mena-Chalco and R. M. Cesar-Jr.},
title = {Protein Coding Regions Identification through the Modified Morlet Transform},
howpublished = {Poster session},
note = {First International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting)},
year = {2005},
month = {04--07 Oct.},
keywords = {Bioinformatics, Protein coding regions indentifications, modified Morlet transform},
abstract = {An important topic in biological sequences analysis is the protein coding
regions identification.
New methods of DNA sequences processing and genes identification can be created
through the \emph{search by content} such sequences. The periodic
pattern of DNA in protein coding regions, called three-base periodicity (TBP),
has been considered proper of coding regions. This phenomenon was not observed
for nonprotein coding regions. The digital signal processing techniques supply a
strong basis for regions identification with TBP.
In this work we introduce a new method for protein coding regions identification
with TBP, based on a newly introduced transform, called Modified Morlet
Transform (MMT), which does not need to be trained on sequence databases.
Preliminary results show that MMT is better than short time Fourier transform (STFT)
by presenting greater sensitivity to TBP and discriminatory capability between
protein coding regions.
{\bf - This is the author's version of the work. Not for redistribution.}},
comment = {Caxambu/MG},
pdf = {pdf/MenaChalco05a.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Protein Coding Regions Identification through the Modified Morlet Transform},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Protein Coding Regions Identification through the Modified Morlet Transform},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Protein Coding Regions Identification through the Modified Morlet Transform},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Protein Coding Regions Identification through the Modified Morlet Transform}
}
@poster{MenaChalco05b,
author = {J. P. Mena-Chalco and R. M. Cesar-Jr.},
title = {Identificação de Regiões Codificantes Através da Transformada Modificada de Morlet},
howpublished = {Poster session},
note = {I Simpósio de Iniciação Científica e Pós-Graduação do IME-USP},
year = {2005},
month = {Oct.},
abstract = {Um tópico importante na área de análise de seqüências biológicas é a busca de genes,
ou seja, a identificação de regiões codificantes de proteínas. A identificação de tais
regiões permite a posterior procura de significado, descrição ou categorização biológica
e construção do mapa do genoma do organismo analisado.
Novos métodos de processamento de seqüências de DNA e de identificação de genes podem ser
criados através da busca de conteúdo (search-by-content) nessas seqüências. As técnicas
de processamento digital de sinais fornecem uma base para a identificação de periodicidade
de três nucleotídeos existentes nas seqüências, isto é, as possíveis regiões codificantes nas
seqüências de DNA.
Nesta trabalho é introduzido um método novo para a identificação dessas regiões, baseado em
uma transformada, denominada Transformada Modificada de Morlet, e são apresentados vários
resultados experimentais obtidos a partir de seqüências de DNA sintéticas e reais.
As principal contribuição do trabalho consiste na criação de um método automático de
identificação de regiões codificantes, que apresenta desempenho superior ao método tradicional
baseado na STFT. O novo método apresenta algumas vantagens importantes em comparação com métodos existentes.
{\bf - This is the author's version of the work. Not for redistribution.}},
comment = {São Paulo/SP},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Identificacao de Regioes Codificantes Atraves da Transformada Modificada de Morlet},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Identificacao de Regioes Codificantes Atraves da Transformada Modificada de Morlet},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Identificacao de Regioes Codificantes Atraves da Transformada Modificada de Morlet},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Identificacao de Regioes Codificantes Atraves da Transformada Modificada de Morlet}
}
@poster{martins_icobi,
author = {D. C. Martins-Jr and R. M. Cesar-Jr. and J. Barrera and G. Goldman},
title = {Genetic network architecture identification by conditional entropy analysis},
howpublished = {Poster session},
note = {ICoBiCoBi - International Conference on Bioinformatics and Computational Biology},
year = {2003},
month = {Maio},
comment = {Ribeirão Preto/SP},
abstract = {A metabolic pathway is a sequence of biochemical reactions mediated by
enzymes, constructed by proteins, generated from RNA, produced by gene
expression in a genetic network. Besides gene expression is also
regulated by proteins. These phenomena pathway constitutes a feedback
system and the genetic networks are called regulatory, since they
define the pathways. Nowadays, expression levels of thousands of
genes can currently be measured simultaneously, thus allowing the
observation of different aspects of system dynamics.
Eukaryotic cells respond to DNA damage by arresting the cell cycle and
modulating gene expression to ensure efficient DNA repair.
Saccharomyces cerevisiae MEC1, the human ATR kinase homolog, plays
central roles in transducing the damage signal. The procedure below
described is being applied to identify genes that belong to the MEC1
hierarquical regulation. We used available microarray data where the
genome-wide expression patterns of wild type cells were compared to
mutants defectivein Mec1 signaling, under normal growth conditions and
in response to the methylating agent metheylmethane sulfonate (MMS)
and ioinizing radiation.
A DDS (Discrete Dynamical System) is a finite set of equations that
describes the sequential
evolution of a vector of discrete variables, called state, under the
action of some discrete external forces, called inputs. The next
state in time t+1 is computed by a function called transition
function, which depends on the states in the previous instants of
time, that is, t, t-1, t-2, ... The transition function is decomposed
in a vector of functions, called component functions, that compute the
transition of each state component.
In this work, we model a genetic network by a DDS, with some random
parameters. The state vector is composed by gene expressions, where
each gene is a component of this vector. The system architecture is
the graph of dependence between genes, i.e. the output and inputs
of the component functions. The goal of this work is to present a
methodology for finding the architecture of a genetic network by
observing time samples of the system dynamics.
Information theory studies random variable dependence by measures such
as conditional entropy and mutual information.
When the independence of two variables increases, the conditional
entropy also increases, since there is less information to concentrate
the mass of the conditional probability. In this work, we explore
this fact by computing conditional entropy between the gene regulated
and the candidate regulatory genes. The entropy of several candidate
regulatory genes is computed and organized in a U-type curve. For a
given regulated gene, the minimum point of the U-curve defines the
regulatory genes.},
pdf = {pdf/martins_icobi.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Genetic network architecture identification by conditional entropy analysis},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Genetic network architecture identification by conditional entropy analysis},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Genetic network architecture identification by conditional entropy analysis},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Genetic network architecture identification by conditional entropy analysis}
}
@poster{martins_icobi2,
author = {J. Barrera and R. M. Cesar-Jr. and D. C. Martins-Jr and
P. J. S. Silva and H. Brentani and E. Osório and S. J. Souza},
title = {Abstract: Dimensionality Reduction for SAGE-based gene identification},
howpublished = {Poster session},
booktitle = {ICoBiCoBi - International Conference on Bioinformatics and Computational Biology},
year = {2003},
month = {Maio},
address = {Ribeirão Preto/SP},
abstract = {This abstract describes an ongoing research on
dimensionality reduction methods applied to SAGE data. The
molecular pathways underlying brain
cancers progression are poorly understood, making the development of
novel diagnostic and therapeutic strategies difficult. Gene
expression patterns are crucial for maintaining and altering
phenotypes of cells. Recent technological advances have resulted in
several widely used methods for large-scale study of gene
expression, including comprehensive open systems, such as SAGE
(Serial Analysis of Gene Expression). SAGE is a method to
efficiently count large numbers of mRNA transcripts by sequencing
short tags, usually 10 bp in length. SAGE Genie uses a new
analytical method of reliably matching SAGE tags to known genes.
SAGE can evaluate the expression patterns of tens of thousands of
genes in a quantitative manner. Using SAGE Genie
(http://cgap.nci.nih.gov/SAGE) we selected 22 brain libraries and
the best tag for each full length represented in that library. SAGE
profiles of 16 brain tumor libraries were compared with SAGE
profiles of 6 normal brain libraries to identify differentially
expressed genes. We constructed a matrix of known genes and their
expression ratio in tumors/ normal SAGE libraries and tried to group
genes with correlated expression profiles across tumor types. We
used 4 different types of brain tumors and 4 different regions of
normal brain.
The data has been normalized through the application of the normal
transform in order to allow the analysis of genes
with low expression profiles. We have used the concept of strong
genes sets introduced recently by Seungchang et. al.
to select differentially expressed genes. A strong
gene set is a small group of genes that can resist to large errors
in the gene expression measurement. Finally, we are using feature
selection algorithms, like sparse support vector machines, to reduce
the processing time and make it manageable by regular desktop
computers.},
pdf = {pdf/martins_icobi2.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Dimensionality Reduction for SAGE-based gene identification},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Dimensionality Reduction for SAGE-based gene identification},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Dimensionality Reduction for SAGE-based gene identification},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Dimensionality Reduction for SAGE-based gene identification}
}
@poster{martins_xmeeting,
author = {J. Barrera and R. M. Cesar-Jr and D. C. Martins-Jr and R. Z. N. Vêncio and C. A. B. Pereira and H. A. del Portillo},
title = {Abstract: Estimation of Probabilistic Genetic Networks of \textit{Plasmodium falciparum} from Dynamical Expression Signals},
howpublished = {Poster session},
note = {First International Conference of the Brazilian Association for Bioinformatics and Computational Biology (X-Meeting)},
booktitle = {1st International Conference of the AB3C (X-meeting)},
year = {2005},
month = {October},
comment = {Caxambu/MG},
abstract = {The advent of genomics into malarial research is
significantly accelerating the discovery of control strategies. Dynamical
global gene expression measures of the intraerythrocytic developmental
cycle (IDC) of the parasite at 1h-scale resolution were recently reported.
Moreover, by using Discrete Fourier Transform based techniques, it
was demonstrated that many genes are regulated in a single periodic manner
which allowed to order genes according to the phase of expression.
In this work we present a framework to construct genetic networks from
dynamical expression signals. The adopted model to represent these
networks is the Probabilistic Genetic Network (PGN). This network is a
Markov chain with some additional properties. This model mimics the
properties of a gene as a non-linear stochastic gate and the systems are
built by coupling of these gates. The PGN estimation is made through the
mean conditional entropy minimization to discover subsets of genes which
perform the best predictions of the target gene in the posterior time
instant. Moreover, a tool that integrates mining of dynamical expression
signals by PGN design techniques, different databases and biological
knowledge, was developed.
The applicability of this tool for discovering gene networks of the
malaria expression regulation system has been validated for simulated
data (http://www.vision.ime.usp.br/CAMDA2004/simulations) and
also for real microarray data using the glycolytic pathway as a ``gold-standard''
(http://www.vision.ime.usp.br/CAMDA2004/glycolysis.html), as well
as by creating an apicoplast as PGN network
(http://www.vision.ime.usp.br/CAMDA2004/apicoplast.html).
As our program creates PGN networks, a negative control was idealized to
further validate the biological value of our findings. Thus, eight
genes, four from glycolysis and four from the apicoplast organelle, were
chosen randomly and used together as seed genes to create PGN networks
based on single-gene and two-gene predictions. The results clearly
demonstrated that the glycolysis and apicoplast PGN networks based on
single-gene predictions were not interconnected
(http://www.vision.ime.usp.br/CAMDA2004/ga_c.html). With the exception of
two genes from the glycolytic PGN network that inter-connected with the
apicoplast PGN network, remaining genes were not connected based on
two-gene predictions
(http://www.vision.ime.usp.br/CAMDA2004/ga2_c.html). Together, this data
demonstrates the value of the PGN model in generating biologically
meaningful networks and which include genes not included by the Fourier approach.},
pdf = {pdf/martins_xmeeting.pdf},
cit1 = {http://scholar.google.com/scholar?as_q=&num=10&btnG=Search+Scholar&as_oq=&as_eq=&as_occt=any&as_sauthors=&as_publication=&as_ylo=&as_yhi=&as_allsubj=all&hl=en&lr=&as_epq=Estimation of Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals},
cit2 = {http://citeseer.ist.psu.edu/cs?cs=1&submit=Documents&co=Citations&cm=50&cf=Any&ao=Citations&am=20&af=Any&q=Estimation of Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals},
cit3 = {http://www.google.com/search?hl=en&btnG=Google+Search&q=Estimation of Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals},
cit4 = {http://www.google.com/cobrand?restrict=crossref&hl=en&btnG=Search&q=Estimation of Probabilistic Genetic Networks of Plasmodium falciparum from Dynamical Expression Signals}
}
@poster{martins_ismb,
author = {J. Barrera and R. M. Cesar-Jr and D. C. Martins-Jr and R. Z. N. Vêncio and C. F. Becerra and C. A. B. Pereira and H. A. del Portillo},
title = {Probabilistic Genetic Networks analysis of three \emph{Plasmodium falciparum} strains from Dynamical Expression Signals},
howpublished = {Poster Session},
note = {14th Annual International Conference On Intelligent Systems For Molecular Biology (ISMB)},
year = {2006},
month = {August},
comment = {Fortaleza/CE - Brazil},
abstract = {The advent of genomics into malarial
research is significantly accelerating the discovery
of control strategies. Dynamical global gene
expression measures of the intraerythrocytic
developmental cycle (IDC) of the parasite at 1h-scale
resolution were recently reported [1]. Moreover, by
using Discrete Fourier Transform based techniques, it
was demonstrated that many genes are regulated in a
single periodic manner which allowed to order genes
according to the phase of expression. In this work we
present a framework to construct genetic networks from
dynamical expression signals [2]. The adopted model to
represent these networks is the Probabilistic Genetic
Network (PGN). This network is a Markov chain with
some additional properties. This model mimics the
properties of a gene as a non-linear stochastic gate
and the systems are built by coupling of these gates.
The PGN estimation is made through the mean
conditional entropy minimization to discover subsets
of genes which perform the best predictions of the
target gene in the posterior time instant. Moreover, a
tool that integrates mining of dynamical expression
signals by PGN design techniques, different databases
and biological knowledge, has been developed. The
applicability of this tool for discovering gene
networks of the malaria expression regulation system
has been validated for simulated data and also for
real microarray data using the glycolytic pathway as a
``gold-standard'', as well as by creating an
apicoplast as PGN network [2].Also, a negative control
between these two modules was confirmed through
construction of PGN networks using four genes from
glycolysis and four from apicoplast organele as seed
genes [2]. Together, this data demonstrates the value
of the PGN model in generating biologically meaningful
networks and which include genes not included by the
Fourier approach [1]. Currently, we are applying the
same technique for three
malarial strains (3D7, Dd2, HB3) in order to analyze
similarities and differences among them and to
discover whether or not these three data sets may be
joint, which would improve the PGN estimation.
[1] M. Llinas, Z. Bozdech, E. D. Wong, A. T. Adai and
J. L. DeRisi. Comparative whole genome transcriptome
analysis of three Plasmodium falciparum strains.
Nucleic Acids Research, 34(4):1166-1173 (2006).
[2] J. Barrera, R. M. Cesar-Jr, D. C. Martins-Jr, R.
Z. N. Vêncio, E. F. Merino, M. M. Yamamoto, F. G.
Leonardi, C. A. B. Pereira and H. A. del Portillo.
Constructing probabilistic genetic networks of
Plasmodium falciparum from dynamical expression
signals of the intraerythrocytic development cycle.
In McConnel, Lin and Hurban, editors, Methods of
Microarray Data Analysis V. Springer, 2005. (in press).},
pdf = {pdf/martins_ismb.pdf}
}
@poster{martins_sib06,
author = {D. C. Martins-Jr and R. M. Cesar-Jr and J. Barrera},
title = {W-operator window design for color texture classification},
howpublished = {Poster Session},
note = {Proceedings of XIX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)},
year = {2006},
month = {August},
comment = {Manaus/AM - Brazil},
abstract = {This work generalizes the technique
described in [1] to image processing applications
based on color. This method chooses a subset of
variables W (i.e. pixels seen through a window) that
maximizes the information observed in a set of
training data by mean conditional entropy
minimization. The task is formalized as a
combinatorial optimization problem, where the search
space is the powerset of the candidate variables and
the measure to be minimized is the mean entropy of the
estimated conditional probabilities. As a full
exploration of the search space requires an enormous
computational effort, an algorithm of the feature
selection literature is applied. The introduced
approach is well fundamented mathematically and
experimental results with color texture recognition
applications show that it is also adequate to treat
problems with color images. Comparative performance
assessment of this technique including an artificial
neural network alternative (Multi-Layer Perceptron)
approach is presented.},
pdf = {pdf/martins_sib06.pdf}
}
@techreport{lopes08a,
author = {F. M. Lopes and D. C. Martins-Jr and R. M. Cesar-Jr},
title = {{DimReduction} - Interactive Graphic Environment for Dimensionality Reduction},
institution = {Instituto de Matem\'{a}tica e Estat\'{i}stica da Universidade de S\~{a}o Paulo and Universidade Tecnol\'{o}gica Federal do Paran\'{a}},
year = {2008},
url = {http://arxiv.org/abs/0805.3964v1},
pdf = {pdf/dimreduction-full.pdf}
}
@techreport{leandro:2008,
author = {J.~J.~G. Leandro and R.~M. {Cesar Jr} and L.~da F. Costa},
title = {{T}echnical {R}eport - Automatic Contour Extraction from 2D Neuron Images},
institution = {Instituto de Matem\'{a}tica e Estat\'{i}stica da Universidade de S\~{a}o Paulo and Instituto de F\'{i}sica de S\~{a}o Carlos - USP - Brazil},
url = {http://aps.arxiv.org/abs/0804.3234},
year = {2008},
month = {April},
pdf = {pdf/jleandro08.pdf}
}
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