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 titleauthorsabstracttypejournalpublished year
DetailsSpeech Enhancement with
Reduction of noise
component in wavelet
domain
Jong Von Seok, Keun Sung
Bae
 Paper  
DetailsSpecial Issue on Vision
Applications and
Technology for
Intelligent Vehicles:
Part
II—Vehicles
ALBERTO BROGGI, KATSUSHI
IKEUCHI, CHARLES E.
THORPE
 Journal PaperIEEE TRANSACTIONS ON
INTELLIGENT
TRANSPORTATION SYSTEMS
2000
DetailsSpecial Issue on Vision
Applications and
Technology for
Intelligent Vehicles:
Part
I—Infrastructur
e
ALBERTO BROGGI, KATSUSHI
IKEUCHI, CHARLES E.
THORPE
 Journal PaperIEEE TRANSACTIONS ON
INTELLIGENT
TRANSPORTATION SYSTEMS
2000
DetailsSpeaker verification: A
tutorial
Jayant M. Naikhttp ieeexplore ieee org xpl abs_free jsp?arNumber=46670
...
Journal PaperIEEE Communications
Magazine
1990
DetailsSpeaker Recognition: A
Tutorial
JOSEPH P. CAMPBELL, JR.,
SENIOR MEMBER, IEEE
 Invited PaperPROCEEDINGS OF THE IEEE,
VOL. 85, NO. 9, SEPTEMBER
1997
 
DetailsSPC in printed circuit
board assembly
j.g. Dobbins and w.j.
Padgett
Statistical process control (SPC) leads to an emphasis
on prevention rather than inspection At NCR Corporation
SPC has been a tool for preventing defects in printed
circuit board assembly A ...
Journalquality progress 
DetailsSpatio-Temporal
Graphical-Model-Based
Multiple Facial Feature
Tracking
Congyong Su, Li HuangIt is challenging to track multiple facial features
simultaneously when rich expressions are presented
on a face We propose a twostep solution In the
first step several independent condensation ...
Journal PaperEURASIP Journal on
Applied Signal Processing
2005:13,
2091–2100
2005
DetailsSPATIAL FREQUENCY DOMAIN
IMAGE PROCESSING FOR
BIOMETRIC
RECOGNITION
B.V.K. Vijaya Kumar,
Marios Savvides, Krithika
Venkataramani,and Chunyan
Xie
 Conference PaperIEEE ICIP 
DetailsSparsity-driven
Ultrasound Imaging
Ahmet Tuysuzoglu,
Jonathan M. Kracht,
Müjdat Çetin, Robin
Cleveland, W. Clem Karl
An image formation framework for ultrasound imaging
from synthetic transducer arrays based on sparsity
driven regularization functionals using single frequency
Fourier domain data is proposed The ...
Journal PaperJournal of the Acoustical
Society of America, vol.
131, no.2, pp. 1271-1281,
February 2012.
2012
DetailsSparsity-Driven Synthetic
Aperture Radar Imaging:
Reconstruction,
Autofocusing, Moving
Targets, and Compressed
Sensing
Müjdat Çetin, Ivana
Stojanovic, N. Ozben
Onhon, Kush R. Varshney,
Sadegh Samadi, W. Clem
Karl, and Alan S. Willsky
This article presents a survey of recent research
on sparsity driven synthetic aperture radar (SAR)
imag ing In particular it reviews 1) the analysis
and synthe sis based sparse signal ...
Journal PaperIEEE Signal Processing
Magazine, vol. 31, no. 4,
pp. 27-40, July 2014
2014
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
DetailsSparsity-driven Image
Formation and
Space-variant Focusing
for SAR
Ozben Onhon, Müjdat
Çetin
In synthetic aperture radar (SAR) imaging the presence
of moving targets in the scene causes phase errors
in the SAR data and subsequently defocusing in the
formed image The defocusing caused by
Conference PaperIEEE International
Conference on Image
Processing, Brussels,
Belgium, September 2011
2011
DetailsSparsity-driven
bandwidth-efficient
decentralized tracking in
visual sensor networks
Serhan Cosar, Müjdat
Çetin
Recent developments in low cost CMOS cameras have
created the opportunity of bringing imaging capabilities
to sensor networks and a new field called visual
sensor networks (VSNs) has emerged VSNs ...
Journal PaperComputer Vision and Image
Understanding, vol. 139,
pp. 40-58, October 2015
2015
DetailsSparsity and Compressed
Sensing in Radar Imaging
Lee Potter, Emre Ertin,
Jason T. Parker, Müjdat
Çetin
Remote sensing with radar is typically an ill posed
linear inverse problem a scene is to be inferred
from limited measurements of scattered electric
fields Parsimonious models provide a ...
Journal PaperProceedings of the IEEE,
vol. 98, no. 6, pp.
1006-1020, June 2010.
2010
DetailsSparsity and Compressed
Sensing in Mono-static
and Multi-static Radar
Imaging
Ivana Stojanovic, Müjdat
Çetin, W. Clem Karl
 Book ChapterCompressed Sensing and
Sparse Filtering, A.
Carmi, L. Mihaylova, and
S. J. Godsill (eds.),
Springer, pp. 395-420,
2014 (ISBN:
978-3642383984)
2014
DetailsSparse Signal
Representation in
Structured Dictionaries
with Application to
Synthetic Aperture Radar
Kush R. Varshney, Müjdat
Çetin, John W. Fisher
III, and Alan S. Willsky
Sparse signal representations and approximations
from overcomplete dictionaries have become an invaluable
tool recently In this paper we develop a new
heuristic graph structured sparse signal ...
Journal PaperIEEE Trans. Signal
Processing, vol. 56, no.
8, pp. 3548-3561, August
2008
2008
DetailsSparse Signal
Representation for
Complex-Valued Imaging
Sadegh Samadi, Müjdat
Çetin, Mohammad Ali
Masnadi-Shirazi
Abstract We propose a sparse signal representation
based method for complexvalued imaging Many coherent
imaging systems such as synthetic aperture radar
(SAR) have an inherent random phase ...
Conference PaperIEEE Signal Processing
Society 13th DSP Workshop
& 5th SPE Workshop,
Marco Island, Florida,
USA, January 2009
2009
DetailsSparse
Representation-Based
Synthetic Aperture Radar
Imaging
Sadegh Samadi, Müjdat
Çetin, Mohammad Ali
Masnadi-Shirazi
There is increasing interest in using synthetic
aperture radar (SAR) images in automated target
recognition and decision making tasks The success
of such tasks depends on how well the ...
Journal PaperIET Radar, Sonar and
Navigation, vol. 5, no.
2, pp. 182-193, February
2011
2011
DetailsSparse Representation
Frameworks for Inference
Problems in Visual Sensor
Networks
Serhan CosarVisual sensor networks (VSNs) form a new research
area that merges computer vision and sensor networks
VSNs consist of small visual sensor nodes called
camera nodes which integrate an image ...
ThesisResearch Database -
Sabanci University
2013
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
 
DetailsSparse Bayesian learning
and the relevance vector
machine
Mike TippingCorrections http research microsoft com MLP
RVM jmlr_typo htm
This paper introduces
a general Bayesian framework for obtaining ...
Journal PaperJournal of Machine
Learning Research
 
DetailsSource localization by
enforcing sparsity
through a Laplacian
prior: an SVD-based
approach
Dmitry M. Malioutov,
Müjdat Çetin, and Alan
S. Willsky
We present a source localization method based upon
a sparse representation of sensor measurements with
an overcomplete basis composed of samples from the
array manifold We enforce sparsity by ...
Conference PaperIEEE Statistical Signal
Processing Workshop
2003
DetailsSome Recent Issues in
Computer Vision
Aytül Erçil Conference PaperProceedings of First Isik
University Signal and
Image Processing Workshop
 
DetailsSolving the 2D puzzle
problem for automated
reconstruction of
archeological findings
(in Turkish)
Ali Yanık, Aytül Erçil Conference PaperProceedings of
SIU’2003
2003
DetailsSolid-model generation
from measured point data
pramod n. Chivate and
andrei g. Jablokow
The paper addresses the issue of solid model generation
from coordinate measuring machine (CMM) point data
All the surfaces of an object are measured with
some in different orientations and ...
Journalcomputer aided design 
DetailsSmart Cameras as
Embedded Systems
Wayne Wolf
Burak Ozer
Tiehan Lv
 Magazin ArticleIEEE Computer Magazin 
DetailsSmall sample size
generalization
Robert P.W. DuinThe generalization of linear classifiers is considered
for training sample sizes smaller than the feature
size It is shown that there exists a good linear
classifier that is better than the ...
PresentationG. Borgefors (eds.),
SCIA'95, Proc. 9th
Scandinavian Conf. on
Image Analysis, Volume 2
 
Detailssmall sample size effects
in statistical pattern
recognition:
recommendations for
practitioners
sarunas j. Raudys and
anil k. Jain
The effects of sample size on feature selection
and error estimation for several types of classifiers
are discussed The focus is on the two class problem
Classifier design in the context of ...
JournalIEEE transactions on
pattern analysis and
machine intelligence
 
DetailsSleepiness/fatigue and
distraction/inattention
as factors for fatal
versus nonfatal
commercial motor vehicle
driver injuries
T.L. Bunn, S. Slavova,
T.W. Struttmann, S.R.
Browning
A retrospective population based case– control
study was conducted to determine whether driver
sleepiness fatigue and inattention distraction
increase the likelihood that a commercial motor
...
Journal PaperAccident Analysis and
Prevention
 
DetailsSleep/Sedation in
Children Undergoing EEG
Testing: A Comparison of
Chloral Hydrate and Music
Therapy
Joanne Loewy, DA, MT-BC,
Cathrine Hallan, Lic
Psych, Eliezer Friedman,
MD, Christine Martinez,
RN, PNP
This study included a total of 60 pediatric patients
ranging from 1 month through 5 years of age The
effects of chloral hydrate and music therapy were
evaluated and compared as means of safe and ...
Journal PaperJournal of PeriAnesthesia
Nursing, Vol 20, No 5
(October), 2005: pp
323-332
2008
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