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 titleauthorsabstracttypejournalpublished year
DetailsIncorporating Complex
Statistical Information
in Active Contour-based
Image Segmentation
Müjdat Çetin, Anthony
Yezzi, Jr., and Alan S.
We propose an information theoretic method for multi
phase image segmentation in an active contour based
framework Our approach is based on nonparametric
density estimates and is able to solve ...
Conference PaperICIP03 - IEEE
International Conference
on Image Processing
DetailsGeometric and
Illumination Invariants
for Object Recognition
Ronald Alferez, Yuan-Fang
We propose invariant formulations that can potentially
be combined into a single system In particular
we describe a framework for computing invariant
features which are insensitive to rigid ...
DetailsNeural Network EnsemblesLars Kai Hansen, Peter
We propose several means for improving the performance
and training of neural networks for classification
We use crossvalidation as a tool for optimizing
network parameters and architecture We ...
JournalIEEE transactions on
pattern analysis and
machine intelligence
DetailsData Association based on
Optimization in Graphical
Models with Application
to Sensor Networks
Lei Chen, Martin
Wainwright, Müjdat
Çetin, and Alan S.
We propose techniques based on graphical models
for efficiently solving data association problems
arising in multiple target tracking with distributed
sensor networks Graphical models provide a ...
Journal PaperMathematical and Computer
Modelling, Special Issue
on Optimization and
Control for Military
DetailsA Unified Framework for
Atlas Matching using
Active Appearance Models
T.F. Cootes, C. Beeston,
G.J. Edwards, C.J. Taylor
We propose to use statistical models of shape and
texture as deformable anatomical atlases By training
on sets of labelled examples these can represent
both the mean structure and appearance of ...
Lecture NotesLecture Notes in Computer
DetailsSemi-Blind Sparse Channel
Estimation with Constant
Modulus Symbols
Müjdat Çetin and Brian
M. Sadler
We propose two methods for estimation of sparse
communication channels In the first method we
consider the problem of channel estimation based
on training symbols and formulate it as an ...
Conference PaperICASSP05 - IEEE
International Conference
on Acoustics, Speech, and
Signal Processing
DetailsFatigue, sleep
restriction and driving
Pierre Philip, Patricia
Sagaspe, Nicholas Moore,
Jacques Taillard, Andre
Charles, Christian
Guilleminault, Bernard
We ran a randomized cross over design study under
sleep deprived and non sleep deprived driving conditions
to test the effects of sleep restriction on real
driving performance The studywas ...
Journal PaperAccident Analysis and
DetailsRegression Modeling in
Back-Propagation and
Projection Pursuit
Jeng-Neng Hwang,
Shyh-Rong Lay, Martin
Maechler, R. Douglas
Martin, James Schimert
We study and compare two types of connectionist
learning methods for model free regression problems
1) the backpropagation learning (BPL) and 2) the
projection pursuit learning (PPL) emerged in ...
JournalIEEE Transactions on
Neural Networks
Detailsdeformation invariants in
object recognition
ehud rivlin and isaac
We study invariance to transformations having two
components The first is an arbitrary large affine
transformation This approximates a viewpoint change
The second is a small but otherwise ...
Journalcomputer vision and image
DetailsA complete implementation
for computing general
dimensional convex hulls
Joannis z. EmirisWe study two important and often complementary
issues in the implementation of geometric algorithms
namely exact arithmetic and degeneracy We focus
on integer arithmetic and propose a general
JournalInternational journal of
computational geometry
& applications
DetailsBoundary detection by
constrained optimization
donald geman, stuart
geman, christine
graffigne, ping dong
We use a statistical framework for finding boundaries
and for partitioning scenes into homogeneous regions
The model is a joint probability distribution for
the array of pixel gray levels and an ...
DetailsNonparametric Shape
Priors for Active
Contour-based Image
Junmo Kim, Müjdat
Çetin, and Alan S.
When segmenting images of low quality or with missing
data statistical prior information about the shapes
of the objects to be segmented can significantly
aid the segmentation process However
Conference PaperEURASIP European Signal
Processing Conference
(EUSIPCO) 2005
DetailsNonparametric Shape
Priors for Active
Contour-based Image
Junmo Kim, Müjdat
Çetin, Alan S. Willsky
When segmenting images of low quality or with missing
data statistical prior information about the shapes
of the objects to be segmented can significantly
aid the segmentation process However ...
Journal PaperSignal Processing, vol.
87, no. 12, pp.
3021-3044, December 2007.
DetailsOne Class Classification
using Implicit Polynomial
Surface Fitting
Ercil, A., Buke, BWhen the number of objects in the training set is
too small for the number of features used most
classification procedures cannot find good classification
boundaries In this paper we introduce
Conference PaperProceedings of ICPR '20022002
DetailsProbabilistic Inference
in Human Sensorimotor
Konrad P. Kording, Daniel
M. Wolpert
When we learn a new motor skill we have to contend
with both the variability inherent in our sensors
and the task The sensory uncertainty can be reduced
by using information about the ...
Paper 2003
DetailsWide-Angle SAR Image
Formation with Migratory
Scattering Centers and
Regularization in Hough
Kush R. Varshney, Müjdat
Çetin, John W. Fisher
III, and Alan S. Willsky
Wide angle synthetic aperture radar imaging presents
numerous challenges but also opportunities to extract
object level information We present a methodology
using an overcomplete dictionary and ...
Conference PaperAdaptive Sensor Array
Processing Workshop
DetailsComprehensive Database
for Facial Expression
Takeo Kanade, Jeffrey F.
Cohn and Yingli Tian
Within the past decade significant effort has occurred
in developing methods of facial expression analysis
Because most investigators have used relatively
limited data sets the ...
DetailsFiltering Using a
Tree-Based Estimator
B. Stenger, A.
Thayananthan, P. H. S.
Torr, R. Cipolla
Within this paper a new framework for Bayesian tracking
is presented which approximates the posterior
distribution at multiple resolutions We propose
a tree based representation of the ...
DetailsSparse kernel principal
component analysis
Michael E. Tipping`Kernel' principal component analysis (PCA) is an
elegant nonlinear generalisation of the popular
linear data analysis method where a kernel function
implicitly defines a nonlinear transformation ...
Conference PaperAdvances in Neural
Information Processing
Systems 13
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