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 titleauthorsabstracttypejournalpublished year
DetailsStatistical methods to
compare the texture
features of machined
surfaces
K. Venkat Ramana, B.
Ramamoorthy
Texture studies play a paramount role in many image
processing applications In this paper an attempt
is made to study the textural features of machined
surfaces (grinding milling and shaping) ...
Journalpattern recognition 
DetailsStatistical Optimization
for 3-D Reconstruction
from a Single View
Kenichi Kanatani,
Yasuyuki Sugaya
 Conference PaperMVA2005 IAPR Conference
on Machine Vision
Applications
 
DetailsStatistical pattern
recognition with neural
networks: benchmarking
studies
Teuvo Kohonen, György
Barna, Ronald Chrisley
Successful recognition of natural signals e g
speech recognition requires substantial statistical
pattern recognition capabilities This is at odds
with the fact that the bulk of work on ...
Conference PaperIEEE International
Conference on Neural
Networks, 1988
 
DetailsStatistical Pattern
Recognition: A Review
Anil K. Jain, Robert P.W.
Duin, Jianchang Mao
The primary goal of pattern recognition is supervised
or unsupervised classification Among the various
frameworks in which pattern recognition has been
traditionally formulated the statistical ...
Paper 1999
DetailsStatistical Region-Based
Segmentation of
Ultrasound Images
Greg Slabaugh, Gozde
Unal, Micheal Wels, Tong
Fang, Bimba Rao
Segmentation of ultrasound images is a challenging
problem due to speckle which corrupts the image
and can result in weak or missing image boundaries
poor signal to noise ratio and diminished ...
Journal PaperUltrasound in Medicine
and Biology [ISSN:
0301-5629], Vol. 35, No.
5, pp. 781–795, 2009
2009
DetailsStatistical Shape
Influence in Geodesic
Active Contours
Michael E. Leventon, W.
Eric L. Grimson, Olivier
Faugeras
A novel method of incorporating shape information
into the image segmentation process is presented
We introduce a representation for deformable shapes
and define a probability distribution over
Conference Paper2000 IEEE Computer
Society Conference on
Computer Vision and
Pattern Recognition
(CVPR'00) - Volume 1
p. 1316
2000
DetailsStent implant follow-up
in intravascular optical
coherence tomography
images
G. Unal, S. Gurmeric,
S.G. Carlier
The objectives of this article are (i) to utilize
computer methods in detection of stent struts imaged
in vivo by optical coherence tomography (OCT) during
percutaneous coronary interventions ...
Journal PaperThe International Journal
of Cardiovascular
Imaging, Published online
first, DOI:
10.1007/s10554-009-9508-4
2009
DetailsStereo based 3D Head Pose
Tracking using the Scale
Invariant Feature
Transform
Batu Akan, Mujdat Cetin,
Aytul Ercil
Turkish title Olcekten Bagimsiz Oznitelik Donusumu
Kullanarak Stereo Kamera ile Uc Boyutlu Kafa Takibi

In this paper a new ...
Conference PaperSIU 2008 - The IEEE 16th
Signal Processing,
Communication and
Applications Conference
(in Turkish)
2008
DetailsStereo based 3d Head Pose
Tracking using the Scale
Invariant Feature
Transform
Batu AkanIn this thesis a new stereo based 3D head tracking
technique based on scale invariant feature transform
(SIFT) features that is robust to illumination
changes is proposed Also two major ...
ThesisSabanci University
Research Database
2008
DetailsStereo Gesture
Recognition Application
unknown Tutorialunknown 
DetailsStereo visionunknown Tutorialunknown 
DetailsStereo Visionunknown Tutorialunknown 
DetailsStochastic Approximations
to Curve Evolution
Equations
A. Yezzi, D. Nain, G.
Unal, A. Tannenbaum, O.
Zeitouni
 Book ChapterMathematical Models of
Computer Vision: The
Handbook
2005
DetailsStochastic Boundary
Estimation and Object
Recognition
D. B. Cooper, H. Elliott,
F. Cohen, L. Reiss, and
P. Symosek
 JournalImage modeling 
DetailsStochastic boundary
estimation and object
recognition
david B. Cooper, h.
Elliott, f. Cohen,
l.reiss, and p. Symosek
 Journalcomputer graphics and
image processing
 
DetailsStochastic Differential
Equations and Geometric
Flows
Gozde Unal, Hamid Krim,
Anthony Yezzi
In recent years curve evolution applied to a single
contour or to the level sets of an image via partial
differential equations has emerged as an important
tool in image processing and ...
Journal PaperIEEE TRANSACTIONS ON
IMAGE PROCESSING
2002
DetailsStochastic relaxation
methods for Image
restoration and expert
systems
Stuart Geman ChapterAutomated Image Analysis:
Theory and experiments /
New York: Academic Press
 
Detailsstochastic relaxation,
gibbs distributions, and
the bayesian restoration
of images
stuart geman and donald
geman
 JournalIEEE transactions on
pattern analysis and
machine intelligence
 
DetailsStructural Descriptions
and inexact Matching
Linda G. Shapiro, Robert
M. Haralick
 JournalIEEE transactions on
pattern analysis and
machine intelligence
 
DetailsStructural Indexing:
Efficient 3-D Object
Recognition
Fridtjof Stein, Gerard
Medioni
 JournalIEEE TRANSACTIONS ON
PATTERN ANALYSIS AND
MACHINE INTELLIGENCE
 
DetailsSTRUCTURED LIGHT BASED
VISION
unknown Presentationunknown 
DetailsStructured LightingReinhard Klette Presentationunknown 
DetailsStudy of Steel Surfaces
using Texture Analysis
Techniques (in Turkish)
Cem Ünsalan, Aytül
Erçil
Bu çalışmada çelik yüzeyler doku analizi
yöntemleri ile incelenmiş yüzey özellikleri
yardımı ile çelik yüzey üzerindeki pas
derecesi bulunmaya ...
Conference PaperProceedings of IEEE
SIU'98
1998
DetailsSubband Domain
Co-Occurrence Matrices
For Texture Defect
Detection
Ahmet Latif Amet, Aysin
Ertüzün, Aytül Erçil
In this paper an efficient algorithm which combines
concepts from wavelet theory and cooccurrence matrices
is presented for detection of defects encountered
in textile images Detection of ...
Journal PaperImage & Vision
Computing
2000
DetailsSubspace based object
recognition using SVM
O.G. Sezer, A. Erçil, M.
Keskinöz
 Conference PaperEUSIPCO 20052005
DetailsSubspace based Super
resolution for Face
Recognition from Video
O.G. Sezer, Y.
Altunbaşak, A. Erçil
 Conference PaperProceedings of SIU 20062006
DetailsSubspace Kernel
Discriminant Analysis for
Speech Recognition
H. ErdoganKernel Discriminant Analysis (KDA) has been successfully
applied to many pattern recognition problems KDA
transforms the original problem into a space of
dimension N where N is the number of ...
Conference PaperRobust 2004 Workshop2005
DetailsSubspace Methods for
Visual Learning and
Recognition
Horst Bischof, Ales
Leonardis
 Tutorial  
DetailsSuper-resolution source
localization through
data-adaptive
regularization
Dmitry M. Malioutov,
Müjdat Çetin, John W.
Fisher III, and Alan S.
Willsky
 Conference PaperAdaptive Sensor Array
Processing Workshop,
Lexington, Massachusetts,
March 2002
2002
DetailsSuper-resolution source
localization through
data-adaptive
regularization
Dmitry M. Malioutov,
Müjdat Çetin, John W.
Fisher, and Alan S.
Willsky
We address the task of source localization using
a novel non parametric data adaptive approach based
on regularized linear inverse problems with sparsity
constraints The class of penalty ...
Conference PaperSAM02 - IEEE Sensor Array
and Multichannel Signal
Processing Workshop
2002
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