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 titleauthorsabstracttypejournalpublished year
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
 
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 ...
Paper  
DetailsComprehensive Database
for Facial Expression
Analysis
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 ...
Paper  
DetailsWide-Angle SAR Image
Formation with Migratory
Scattering Centers and
Regularization in Hough
Space
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
2006
DetailsProbabilistic Inference
in Human Sensorimotor
Processing
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
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
DetailsNonparametric Shape
Priors for Active
Contour-based Image
Segmentation
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.
2007
DetailsNonparametric Shape
Priors for Active
Contour-based Image
Segmentation
Junmo Kim, Müjdat
Çetin, and 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
Conference PaperEURASIP European Signal
Processing Conference
(EUSIPCO) 2005
2005
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 ...
JournalIEEE TRANSACTIONS ON
PATTERN ANALYSIS AND
MACHINE INTELLIGENCE
 
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
 
Detailsdeformation invariants in
object recognition
ehud rivlin and isaac
weiss
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
understanding
 
DetailsRegression Modeling in
Back-Propagation and
Projection Pursuit
Learning
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
 
DetailsFatigue, sleep
restriction and driving
performance
Pierre Philip, Patricia
Sagaspe, Nicholas Moore,
Jacques Taillard, Andre
Charles, Christian
Guilleminault, Bernard
Bioulac
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
Prevention
 
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
2005
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
Science
1999
DetailsData Association based on
Optimization in Graphical
Models with Application
to Sensor Networks
Lei Chen, Martin
Wainwright, Müjdat
Çetin, and Alan S.
Willsky
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
Applications
2006
DetailsNeural Network EnsemblesLars Kai Hansen, Peter
Salamon
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
 
DetailsGeometric and
Illumination Invariants
for Object Recognition
Ronald Alferez, Yuan-Fang
Wang
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 ...
Paper  
DetailsIncorporating Complex
Statistical Information
in Active Contour-based
Image Segmentation
Müjdat Çetin, Anthony
Yezzi, Jr., and Alan S.
Willsky
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
2003
DetailsSparsity-Driven
Sparse-Aperture
Ultrasound Imaging
Müjdat Çetin, Emmanuel
Bossy, Robin Cleveland,
and W. Clem Karl
We propose an image formation algorithm for ultrasound
imaging based on sparsity driven regularization
functionals We consider data collected by synthetic
transducer arrays with the primary ...
Conference PaperIEEE International
Conference on Acoustics,
Speech, and Signal
Processing 2006
2006
DetailsEye Tracking Using Markov
Models
A. M. Bagci, R. Ansari,
A. Khokhar, E. Cetin
We propose an eye detection and tracking method
based on color and geometrical features of the human
face using a monocular camera In this method a
decision is made on whether the eyes are closed
Journal PaperIEEE2004
DetailsEnhanced, high resolution
radar imaging based on
robust regularization
Müjdat Çetin, W. Clem
Karl
We propose an enhanced image reconstruction method
for spotlight mode synthetic aperture radar (SAR)
Our approach involves extension of feature preserving
regularization techniques developed in ...
Conference PaperICASSP00 - IEEE
International Conference
on Acoustics, Speech, and
Signal Processing
2000
DetailsBoundary Finding with
Correspondence Using
Statistical Shape Models
Yongmei Wang and Lawrence
H. Staib
We propose an approach for boundary ¯nding where
the correspondence of a subset of boundary points
to a model is simultaneously determined Global
shape parameters derived from the statistical ...
Conference PaperProc. IEEE Conf. Computer
Vision and Pattern
Recognition, pp. 338-345,
1998
1998
DetailsAR-PCA-HMM Approach for
Sensorimotor Task
Classification in
EEG-based Brain-Computer
Interfaces
Ali Ozgur Argunsah,
Müjdat Çetin
We propose an approach based on Hidden Markov models
(HMMs) combined with principal component analysis
(PCA) for classification of four class single trial
motor imagery EEG data for brain ...
Conference PaperInternational Conference
on Pattern Recognition,
Istanbul, Turkey, August
2010
2010
DetailsBoundary Finding with
Prior Shape and
Smoothness Models
Yongmei Wang, Lawrence H.
Staib
We propose a unified framework for boundary finding
where a Bayesian formulation based on prior knowledge
and the edge information of the input image (likelihood)
is employed The prior ...
Journal PaperIEEE TRANSACTIONS ON
PATTERN ANALYSIS AND
MACHINE INTELLIGENCE,
VOL. 22, NO. 7, JULY 2000
2000
DetailsA Shape-Based Approach to
the Segmentation of
Medical Imagery Using
Level Sets
Andy Tsai, Anthony Yezzi,
Jr., William Wells, Clare
Tempany, Dewey Tucker,
Ayres Fan, W. Eric
Grimson, and Alan Willsky
We propose a shape based approach to curve evolution
for the segmentation of medical images containing
known object types In particular motivated by
the work of Leventon Grimson and Faugeras ...
Journal PaperIEEE TRANSACTIONS ON
MEDICAL IMAGING, VOL. 22,
NO. 2, FEBRUARY 2003
2003
DetailsShape Retrieval Based on
Dynamic Programming
Evangelos Milios,
Euripides G.M. Petrakis
We propose a shape matching algorithm for deformed
shapes based on dynamic programming Our algorithm
is capable of grouping together segments at finer
scales in order to come up with appropriate ...
Journal PaperIEEE Transactions on
Image Processing, Special
Issue on Image and Video
Processing for Digital
Libraries
2000
DetailsShape and data-driven
texture segmentation
using local binary
patterns
Tekeli, Erkin and Çetin,
Müjdat and Erçil,
Aytül
We propose a shape and data driven texture segmentation
method using local binary patterns (LBP) and active
contours In particular we pass textured images
through a new LBP based filter which ...
Conference PaperEUSIPCO 20072007
DetailsSuperresolution and
edge-preserving
reconstruction of
complex-valued synthetic
aperture radar images
Müjdat Çetin and W.
Clem Karl
We propose a regularization basedmethod for the
complexvalued synthetic aperture radar (SAR) image
formation problem The method can produce images
with higher resolution than that supported by
Conference PaperICIP00 - IEEE
International Conference
on Image Processing
2000
DetailsLearning the Dynamics and
Time-Recursive Boundary
Detection of Deformable
Objects
Walter Sun, Müjdat
Çetin, Raymond Chan, and
Alan S. Willsky
We propose a principled framework for recursively
segmenting deformable objects across a sequence
of frames We demonstrate the usefulness of this
method on left ventricular segmentation across a
...
Journal PaperIEEE Trans. Image
Processing, vol. 17, no.
11, pp. 2186-2200,
November 2008
2008
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